Real-time multi-model decadal climate predictions

We present the first climate prediction of the coming decade made with multiple models, initialized with prior observations. This prediction accrues from an international activity to exchange decadal predictions in near real-time, in order to assess differences and similarities, provide a consensus view to prevent over-confidence in forecasts from any single model, and establish current collective capability. We stress that the forecast is experimental, since the skill of the multi-model system is as yet unknown. Nevertheless, the forecast systems used here are based on models that have undergone rigorous evaluation and individually have been evaluated for forecast skill. Moreover, it is important to publish forecasts to enable open evaluation, and to provide a focus on climate change in the coming decade. Initialized forecasts of the year 2011 agree well with observations, with a pattern correlation of 0.62 compared to 0.31 for uninitialized projections. In particular, the forecast correctly predicted La Niña in the Pacific, and warm conditions in the north Atlantic and USA. A similar pattern is predicted for 2012 but with a weaker La Niña. Indices of Atlantic multi-decadal variability and Pacific decadal variability show no signal beyond climatology after 2015, while temperature in the Niño3 region is predicted to warm slightly by about 0.5 °C over the coming decade. However, uncertainties are large for individual years and initialization has little impact beyond the first 4 years in most regions. Relative to uninitialized forecasts, initialized forecasts are significantly warmer in the north Atlantic sub-polar gyre and cooler in the north Pacific throughout the decade. They are also significantly cooler in the global average and over most land and ocean regions out to several years ahead. However, in the absence of volcanic eruptions, global temperature is predicted to continue to rise, with each year from 2013 onwards having a 50 % chance of exceeding the current observed record. Verification of these forecasts will provide an important opportunity to test the performance of models and our understanding and knowledge of the drivers of climate change.     

Reconstruction of RHESSI Solar Flare Images with a Forward Fitting Method

We describe a forward-fitting method that has been developed to reconstruct hard X-ray images of solar flares from the Ramaty High-Energy Solar Spectroscopic Imager (RHESSI), a Fourier imager with rotation-modulated collimators that was launched on 5 February 2002. The forward-fitting method is based on geometric models that represent a spatial map by a superposition of multiple source structures, which are quantified by circular gaussians (4 parameters per source), elliptical gaussians (6 parameters), or curved ellipticals (7 parameters), designed to characterize real solar flare hard X-ray maps with a minimum number of geometric elements. We describe and demonstrate the use of the forward-fitting algorithm. We perform some 500 simulations of rotation-modulated time profiles of the 9 RHESSI detectors, based on single and multiple source structures, and perform their image reconstruction. We quantify the fidelity of the image reconstruction, as function of photon statistics, and the accuracy of retrieved source positions, widths, and fluxes. We outline applications for which the forward-fitting code is most suitable, such as measurements of the energy-dependent altitude of energy loss near the limb, or footpoint separation during flares. Supplementary material to this paper is available in electronic form at http://dx.doi.org/10.1023/A:1022469811115     

Pseudostalaktiten und Verwandtes

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Beiträge zur Geochemie

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Begriff und Bedeutung der Intrusionstektonik

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Residual drift demands in moment‐resisting steel frames subjected to narrow‐band earthquake ground motions

This paper presents the main results of the evaluation of residual inter‐story drift demands in typical moment‐resisting steel buildings designed accordingly to the Mexican design practice when subjected to narrow‐band earthquake ground motions. Analytical 2D‐framed models representative of the study‐case buildings were subjected to a set of 30 narrow‐band earthquake ground motions recorded on stations placed in soft‐soil sites of Mexico City, where most significant structural damage was found in buildings as a consequence of the 1985 Michoacan earthquake, and scaled to reach several levels of intensity to perform incremental dynamic analyses. Thus, results were statistically processed to obtain hazard curves of peak (maximum) and residual drift demands for each frame model. It is shown that the study‐case frames might exhibit maximum residual inter‐story drift demands in excess of 0.5%, which is perceptible for building's occupants and could cause human discomfort, for a mean annual rate of exceedance associated to peak inter‐story drift demands of about 3%, which is the limiting drift to avoid collapse prescribed in the 2004 Mexico City Seismic Design Provisions. The influence of a member's post‐yield stiffness ratio and material overstrength in the evaluation of maximum residual inter‐story drift demands is also discussed. Finally, this study introduces response transformation factors, T_p, that allow establishing residual drift limits compatible with the same mean annual rate of exceedance of peak inter‐story drift limits for future seismic design/evaluation criteria that take into account both drift demands for assessing a building's seismic performance. Copyright © 2013 John Wiley & Sons, Ltd.     

Crustal observations beneath the southern North Sea and their tectonic and geological implications

In 1991, a deep seismic reflection line, MPNI-9101, was acquired in the southern North Sea from the Mesozoic Broad Fourteens Basin, across the West Netherlands Basin onto the London-Brabant Massif (LBM). The resultant section shows a strongly reflective lower crust beneath the area of Mesozoic basin development. This lower crustal reflectivity continues to be strong beneath the LBM. The travel time to the base of the reflective zone increases from approximately 11.0 s beneath the Mesozoic basins to 12.5 s beneath the LBM, suggesting a southward thickening of the crust (Rijkers et al., 1993). Based on these travel times and information from deep wells and refraction surveys. Moho depth is estimated to increase from about 31 km beneath the Mesozoic basins to about 38 km beneath the LBM. This difference in depth to the Moho can partly be explained by coaxial stretching of the crust beneath the Mesozoic basins. In comparison with the Mesozoic basins, the crust beneath the LBM was thickened during the Caledonian and Variscan orogenies.     

Statistical decadal predictions for sea surface temperatures: a benchmark for dynamical GCM predictions

Accurate decadal climate predictions could be used to inform adaptation actions to a changing climate. The skill of such predictions from initialised dynamical global climate models (GCMs) may be assessed by comparing with predictions from statistical models which are based solely on historical observations. This paper presents two benchmark statistical models for predicting both the radiatively forced trend and internal variability of annual mean sea surface temperatures (SSTs) on a decadal timescale based on the gridded observation data set HadISST. For both statistical models, the trend related to radiative forcing is modelled using a linear regression of SST time series at each grid box on the time series of equivalent global mean atmospheric CO₂ concentration. The residual internal variability is then modelled by (1) a first-order autoregressive model (AR1) and (2) a constructed analogue model (CA). From the verification of 46 retrospective forecasts with start years from 1960 to 2005, the correlation coefficient for anomaly forecasts using trend with AR1 is greater than 0.7 over parts of extra-tropical North Atlantic, the Indian Ocean and western Pacific. This is primarily related to the prediction of the forced trend. More importantly, both CA and AR1 give skillful predictions of the internal variability of SSTs in the subpolar gyre region over the far North Atlantic for lead time of 2–5 years, with correlation coefficients greater than 0.5. For the subpolar gyre and parts of the South Atlantic, CA is superior to AR1 for lead time of 6–9 years. These statistical forecasts are also compared with ensemble mean retrospective forecasts by DePreSys, an initialised GCM. DePreSys is found to outperform the statistical models over large parts of North Atlantic for lead times of 2–5 years and 6–9 years, however trend with AR1 is generally superior to DePreSys in the North Atlantic Current region, while trend with CA is superior to DePreSys in parts of South Atlantic for lead time of 6–9 years. These findings encourage further development of benchmark statistical decadal prediction models, and methods to combine different predictions.