A three-level framework for multi-risk assessment

The effective management of the risks posed by natural and man-made hazards requires all relevant threats and their interactions to be considered. This paper proposes a three-level framework for multi-risk assessment that accounts for possible hazard and risk interactions. The first level is a flow chart that guides the user in deciding whether a multi-hazard and risk approach is required. The second level is a semi-quantitative approach to explore if a more detailed, quantitative assessment is needed. The third level is a detailed quantitative multi-risk analysis based on Bayesian networks. Examples that demonstrate the application of the method are presented.     

Accounting for the solar radiation in thermal regime prediction for railway subgrade in cold regions

This paper presents a comparative analysis of simulation processes of seasonal freezing-thawing of railway subgrade and permafrost degradation, with and without accounting for solar radiation. Also, the effect of sun screens to reduce the degradation of subgrade permafrost under different climatic conditions is numerically substantiated. And finally, the temperature criterion of the origination of permafrost is illustrated.     

The Central Bundelkhand Archaean greenstone complex,Bundelkhand craton,central India: geology,composition, and geochronology of supracrustal rocks

Analysis of 3.3 Ga tonalite–trondhjemite–granodiorite (TTG) series granitoids and greenstone belt assemblages from the Bundelkhand craton in central India reveal that it is a typical Archaean craton. At least two greenstone complexes can be recognized in the Bundelkhand craton, namely the (i) Central Bundelkhand (Babina, Mauranipur belts) and (ii) Southern Bundelkhand (Girar, Madaura belts). The Central Bundelkhand greenstone complex contains three tectonostratigraphic assemblages: (1) metamorphosed basic or metabasic, high-Mg rocks; (2) banded iron formations (BIFs); and (3) felsic volcanics. The first two assemblages are regarded as representing an earlier sequence, which is in tectonic contact with the felsic volcanics. However, the contact between the BIFs and mafic volcanics is also evidently tectonic. Metabasic high-Mg rocks are represented by amphibolites and tremolite-actinolite schists in the Babina greenstone belt and are comparable in composition to tholeiitic basalts-basaltic andesites and komatiites. They are very similar to the metabasic high-Mg rocks of the Mauranipur greenstone belt. Felsic volcanics occur as fine-grained schists with phenocrysts of quartz, albite, and microcline. Felsic volcanics are classified as calc-alkaline dacites, less commonly rhyolites. The chondrite-normalized rare earth element distribution pattern is poorly fractionated (La_N/Lu_N = 11–16) with a small negative Eu anomaly (Eu/Eu* = 0.68–0.85), being characteristic of volcanics formed in a subduction setting. On Rb – Y + Nb, Nb – Y, Rb – Ta + Yb and Ta – Yb discrimination diagrams, the compositions of the volcanics are also consistent with those of felsic rocks formed in subduction settings. SHRIMP-dating of zircon from the felsic volcanics of the Babina belt of the Central Bundelkhand greenstone complex, performed for the first time, has shown that they were erupted in Neoarchaean time (2542 ± 17 Ma). The early sequence of the Babina belt is correlatable with the rocks of the Mauranipur belt, whose age is tentatively estimated as Mesoarchaean. The Central Bundelkhand greenstone complex consists of two (Meso- and Neoarchaean) sequences, which were formed in subduction settings.     

Global increase in record-breaking monthly-mean temperatures

The last decade has produced record-breaking heat waves in many parts of the world. At the same time, it was globally the warmest since sufficient measurements started in the 19th century. Here we show that, worldwide, the number of local record-breaking monthly temperature extremes is now on average five times larger than expected in a climate with no long-term warming. This implies that on average there is an 80 % chance that a new monthly heat record is due to climatic change. Large regional differences exist in the number of observed records. Summertime records, which are associated with prolonged heat waves, increased by more than a factor of ten in some continental regions including parts of Europe, Africa, southern Asia and Amazonia. Overall, these high record numbers are quantitatively consistent with those expected for the observed climatic warming trend with added stationary white noise. In addition, we find that the observed records cluster both in space and in time. Strong El Niño years see additional records superimposed on the expected long-term rise. Under a medium global warming scenario, by the 2040s we predict the number of monthly heat records globally to be more than 12 times as high as in a climate with no long-term warming.     

Climate change and infectious diseases: Can we meet the needs for better prediction?

The next generation of climate-driven, disease prediction models will most likely require a mechanistically based, dynamical framework that parameterizes key processes at a variety of locations. Over the next two decades, consensus climate predictions make it possible to produce forecasts for a number of important infectious diseases that are largely independent of the uncertainty of longer-term emissions scenarios. In particular, the role of climate in the modulation of seasonal disease transmission needs to be unravelled from the complex dynamics resulting from the interaction of transmission with herd immunity and intervention measures that depend upon previous burdens of infection. Progress is also needed to solve the mismatch between climate projections and disease projections at the scale of public health interventions. In the time horizon of seasons to years, early warning systems should benefit from current developments on multi-model ensemble climate prediction systems, particularly in areas where high skill levels of climate models coincide with regions where large epidemics take place. A better understanding of the role of climate extremes on infectious diseases is urgently needed.     

The Indo-Australian monsoon and its relationship to ENSO and IOD in reanalysis data and the CMIP3/CMIP5 simulations

A large spread exists in both Indian and Australian average monsoon rainfall and in their interannual variations diagnosed from various observational and reanalysis products. While the multi model mean monsoon rainfall from 59 models taking part in the Coupled Model Intercomparison Project (CMIP3 and CMIP5) fall within the observational uncertainty, considerable model spread exists. Rainfall seasonality is consistent across observations and reanalyses, but most CMIP models produce either a too peaked or a too flat seasonal cycle, with CMIP5 models generally performing better than CMIP3. Considering all North-Australia rainfall, most models reproduce the observed Australian monsoon-El Niño Southern Oscillation (ENSO) teleconnection, with the strength of the relationship dependent on the strength of the simulated ENSO. However, over the Maritime Continent, the simulated monsoon-ENSO connection is generally weaker than observed, depending on the ability of each model to realistically reproduce the ENSO signature in the Warm Pool region. A large part of this bias comes from the contribution of Papua, where moisture convergence seems to be particularly affected by this SST bias. The Indian summer monsoon-ENSO relationship is affected by overly persistent ENSO events in many CMIP models. Despite significant wind anomalies in the Indian Ocean related to Indian Ocean Dipole (IOD) events, the monsoon-IOD relationship remains relatively weak both in the observations and in the CMIP models. Based on model fidelity in reproducing realistic monsoon characteristics and ENSO teleconnections, we objectively select 12 “best” models to analyze projections in the rcp8.5 scenario. Eleven of these models are from the CMIP5 ensemble. In India and Australia, most of these models produce 5–20 % more monsoon rainfall over the second half of the twentieth century than during the late nineteenth century. By contrast, there is no clear model consensus over the Maritime Continent.