Extreme events

Figure 4.24 A loading stress distribution with extreme events...

Sanchez E, Gallardo C, Gaertner MA, Arribas A, Castro M (2004) Future climate extreme events in the Mediterranean simulated by a regional climate model a first approach. Glob Planet Change 44 163-180... 

Beniston M, Stephenson DB, Christensen OB, Ferro CAT, Frei C, Gollete S, Halsnaes K, Holt T, Jylha K, Koffi B, Palutikof J, Scholl R, Semmler T, Woth K (2007) Future extreme events in European climate an exploration of regional climate model projections. Clim Change 81 71-95. doi 10.1007/ sl0584-006-9226-z... 

Ek osystem recovery from environmental extremes The examples which illustrated the responses of agricultural ecosystems to extreme events have been limited to short-term effects on productivity. For natural ecosystems which can not be replanted the recovery response to an environmental extreme is crucial, not only in the time taken for recovery but also in terms of the manner in which the ecosystem may change during and after the period of recovery. In this context, change is particularly concerned with the species which constitute an ecosystem, a consideration which is central to the aims of conservation. 

The extreme events which have been discussed differ in their characteristic spatial scales of importance. Each event which causes wind-throw occurs on a smaller spatial scale than a pollution event, as recently seen by the very extensive scale of the Chernobyl fallout (Johnston, 1987). At an even greater scale, the projected extent of the nuclear winter will be global (Covey, 1987). Examples of this hierarchy of scales of events are shown in Table 1. 

These scales of extent define the manner in which the ideas of extreme events are applicable to agriculture and forestry. Wind-throw is a small-scale process and the forest manager must grow and manage plantation forests which will survive extreme wind speeds at the spatial scale of his plantation. The question is, how rare must this extreme event be, before it may be discounted. The answer is likely to be dominated by economics and also the longevity of the plants with a 50 year harvesting interval, it seems clear that the return periods of extreme events up to 50 years (at least) are crucial. 

The scientific literature on PCP use and crime is sparse and consists mainly of case studies of persons who have committed violent, often bizarre acts after ingesting the drug (Siegel 1978 Siegel 1980 Fauman and Fauman 1982). Death from drowning, often in small amounts of water, has been a frequent cause of PCP -related death in California, and the media s emphasis on such extreme events has helped to increase the drug s notoriety. 

On the other extreme, events that are minor (consequence category 1, as indicated in Table 5.3 or 5.6) receive a risk priority of IV, although they may be likely to occur. Because of the low severity of the consequences, further evaluation need not be considered. 

The ET cover cannot be tested at every landfill site so it is necessary to extrapolate the results from sites of known performance to specific landfill sites. The factors that affect the hydrologic design of ET covers encompass several scientific disciplines and there are numerous interactions between factors. As a consequence, a comprehensive computer model is needed to evaluate the ET cover for a site.48 The model should effectively incorporate soil, plant, and climate variables, and include their interactions and the resultant effect on hydrology and water balance. An important function of the model is to simulate the variability of performance in response to climate variability and to evaluate cover response to extreme events. Because the expected life of the cover is decades, possibly centuries, the model should be capable of estimating long-term performance. In addition to a complete water balance, the model should be capable of estimating long-term plant biomass production, need for fertilizer, wind and water erosion, and possible loss of primary plant nutrients from the ecosystem. 

Conservative is used to define orchard and management factors that once introduced cannot, or are extremely difficult to, change or require substantial additional investment to do so. Among these are soil and other site-specific conditions, choice of variety/cultivar and rootstock, planting density and tree canopy formation, system stabilisation measures at orchard set-up and installations to buffer extreme events. 

The bias-correction is necessary to correct both the absolute magnitude and the seasonal cycle to that of the observations. This approach assumes that the same model biases persist in the future climate and thus GCMs more accurately simulate relative change than absolute values. It provides a correction of monthly mean climate only and does not correct biases in higher order statistics including the simulation of extreme events and persistence. 

Wet-weather processes are subject to high variability. A simple deterministic model result in terms of the impacts on the water quality is out of scope. From a modeling point of view, a stochastic description is a realistic solution for producing relevant results. Furthermore, an approach based on a historical rainfall series as model input is needed to establish extreme event statistics for a critical CSO impact that can be compared to a water quality criterion. In terms of CSO design including water quality, this approach is a key point. 

Hot and dry meteorological conditions in summer increase the extent of observed biomass fires. For example, the summer of 2010 was exceptionally warm in Eastern Europe and large parts of Russia. With climate change such extreme events are predicted to increase and by the end of the century heat waves of this magnitude are expected to occur every decade [50]. For European Arctic the transport of smokes from more frequent biomass fires may affect the global climate change. Whether the Arctic is getting warmer or colder because of the smoke events is still under evaluation. 

In connection with the great interest in potential extreme events, IPCC (2001, 2007) contain respective prognostic estimates for comparison with present observations (Table 7.5). This was discussed in detail by Grigoryev and Kondratyev (2001c) and Kondratyev (1998b). Vagueness of the tabulated conclusions is explained by scarce observational data and unreliable numerical modeling results. 

Shipitalo, M.J. and L.B. Owens (2006). Tillage system, application rate, and extreme event effects on herbicide losses in surface runoff. J. Environ. Qual., 35 2186-2194. 

Body temperature is a very important clinical marker as slight alterations in temperature can alter cell function and in extreme events cause death. Cell metabolism results in the generation of heat energy this is lost from the body via radiation, evaporation, conduction and convection. The hypothalamus is responsible for controlling body temperature. 

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