3. El capitalismo y la configuración de espacios geográficos
3.3 Crisis de reconfiguraciones espaciales a finales del S. XX
The earlier section described the average global water cycle. However, the water cycle varies both spatially and temporally, as we are all well aware when we witness floods and droughts. The Intergovernmental Panel for Climate Change defines climate variability as ‘variations in the mean state and other statistics (such as standard deviations, the occurrence of extremes, etc.) of the climate on all spatial and temporal scales beyond that of individual weather events’. An extreme weather event is an event that is ‘as rare as or rarer than the 10th or 90th percentile of the observed probability density function’ (IPCC, 2007a). Climate extreme events occur when ‘a pattern of extreme weather persists for some time, such as a season, especially if it yields an average or total that is itself extreme (e.g., drought or heavy rainfall over a season)’ (IPCC, 2001). Here we will give examples of climate variability at multiple scales, relevant to the global water cycle, including extreme climate events and varia bility at multi-annual and multi-decadal scales.
1 Extremes
The summer heatwave of 2003 across western Europe was an extreme climate event. Areas experi enced elevated temperatures of 3.5°C and below-average precipitation. Across Europe,
REFLECTIVE QUESTION
What are the different processes that can result in rainfall?
30,000 to 50,000 deaths were attributed to this heatwave (Fedoroff et al., 2010), gross primary productivitydeclined by 30% (Ciais et al., 2005), and crop yields of grains and fruits were reduced by 20–36% (Fedoroff et al., 2010). By studying the conditions surrounding the heatwave we can learn about feedbacks that make extreme events more extreme. Reduced evapotranspiration, due to the dry land surface conditions, prevented surface cooling, and thus even higher tempera - tures resulted; a positive feedback. Teuling et al. (2010) showed how initial heating was suppressed more over grasslands than forests because of en - hanced evaporation; however, the more conserva - tive use of soil moisture by forests mitigates extreme heat over the longer term. It is also important to consider the effect of soil moisture on precipitation. Figure 2.4 shows the land– atmosphere coupling strength for the northern
summer. Land–atmosphere coupling is parti - cularly strong across the Great Plains, Sahel and South Asia (Koster et al., 2004). Where such coupling occurs it is likely that when there is low soil moisture there is little supply to the atmos - phere and dry conditions are enhanced. Such feedbacks may exacerbate (intensify and/or pro - long) extreme conditions. Both soil moisture– temperature, and soil moisture–precipitation feedbacks are likely to be more important in Europe under future climate change (Seneviratne et al., 2006).
Extreme events occurred in the summer of 2010 across central Europe, with drought, leading to fires, especially in peatlands, with smoke lead - ing to a deterioration of air quality in places such as Moscow. Concurrently there were catas - trophic floods across Pakistan. Both were associ - ated with the same breakdown in the normal
Figure 2.4 Land–atmosphere coupling strength in June, July and August. The units are dimensionless and just provide a relative picture of where coupling is greatest.
Source: Adapted from Koster, R.D. et al. 2004. Regions of strong coupling between soil moisture and precipitation. Science 305: 1138–1140. Reprinted with permission from AAAS.
flow of the jet stream(high-velocity winds at the top of the lower atmosphere), as explained within
Figure 2.5. Patterns in the upper troposphere can be important for determining extreme events and variability from year to year, as described in
Box 2.1.
Modelling results provide evidence for a human contribution to more intense precipi - tation extremes over the northern hemisphere during the last 50 years (Min et al., 2011), and
probabilistic techniques are now used to attri- bute a contribution of anthropogenic climate change to increased flood risk, for example, during the UK floods in autumn 2000 (Pall et al., 2011; Allan, 2011). For example, from results
based on climate model simulations, Pall et al. (2011) stated: ‘The precise magnitude of the anthro pogenic contribution remains uncertain, but in nine out of ten cases our model results indicate that twentieth-century anthropogenic greenhouse gas emissions increased the risk of floods occurring in England and Wales in autumn 2000 by more than 20%, and in two out of three cases by more than 90%.’
2 Multi-annual timescales
El Niño Southern Oscillation (ENSO) is import - ant for climate variability and extremes across large parts of the world, through a process called teleconnections (Bjerknes, 1969). ENSO is a modi fication of the ocean and atmospheric circulation in the equatorial pacific region, and occurs irregularly at a frequency of three to six years and with varying intensity.
In normal conditions (Figure 2.7a), warm water stacks up in the western Pacific, maintained by the easterly (from the east) surface trade winds. The warm water evaporates, producing the large convective rainfall systems over the western Pacific. The waters in the east are cool through evaporation and upwelling of cold, nutrient-rich water from below. During El Niño conditions the easterly winds slow and the body of warm water is shifted eastwards. Rainfall shifts eastwards, leaving the western Pacific region drier than normal, and heavy rainfall occurs over Peru. Upwelling of the cold, nutrient-rich water near the eastern Pacific coast weakens, and leads to drastic reductions in the anchovy populations (and thus harvest); the name, El Niño, is Spanish for ‘the boy-child’, and the term given by Peruvian fishermen, in reference to the Christ child, as this phenomenon starts around Christmas time. La Niña is essentially a shift in the ocean atmos - phere circulation in the opposite direction, with stronger trade winds, a greater buildup of warm waters in the western Pacific, with heavier than normal rains in the western Pacific region.
Figure 2.5 The static jet stream of summer 2010, which led to different extreme events across Europe and Asia. The temperature anomalies shown on the map are from 20–27 July 2010 compared to temperatures for the same dates from 2000 to 2008. The anomalies are based on land surface tem pera tures observed by the Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA’s Terra sate - llite. Areas with above-average temperatures appear in red and orange, and areas with below-average temperatures appear in shades of blue.
Source: From NASA/Earth Observatory; NASA image has been altered.