Community Paper on Climate Extremes
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Detection and attribution studies examining whether human influence has played a role in changes in cyclone number, intensity or distribution have not yet been conducted. However, human influence has been detected in the global sea level pressure (Gillett et al, 2005; Gillett and Stott, 2009) and in one study, in geostrophic wind energy derived from sea level pressure records (Wang et al, 2009b). Gillett and Stott (2009) show that observed patterns of trends, which indicate decreases in high latitude sea level pressure and increases elsewhere, is robust when calculated from data for 1949-2009. Observed changes were consistent with expectations based on the model (HadGEM1) used in that study, suggesting that anthropogenic influence has contributed to both pressure decreases at high latitudes and increases at low latitudes. The mechanism for the latter is not well understood. Using an approach that would not formally be considered to a detection and attribution method, Fogt et al (2009) find that both coupled climate model simulated trends and observed trends in the Southern Annular Mode (SAM) lie outside the range of internal climate variability during the austral summer, suggesting that human influence has contributed to the observed SAM trends. Tropical cyclones About 90 tropical cyclones have been observed annually since the introduction of geostationary satellites. The global frequency has remained more or less constant over this period, albeit with substantial variability in the frequency of tropical cyclones and locations of their tracks within individual ocean basins (e.g., Webster et al., 2005; Kossin et al., 2010). Tropical cyclones are typically classified in terms of their intensity according to the Saffir-Simpson scale as indicated by near-surface wind speed or central pressure. Long-term records of the strongest storms are potentially less reliable than those of tropical cyclones in general (Landsea et al, 2006). In addition to intensity, other impact-relevant characteristics of tropical cyclones include frequency, duration, track, precipitation, and the structure and areal extent of the wind field in tropical cyclones, the latter of which can be very important for damage through storm surge as well as the direct wind-related damage. Forming robust physical links between changes in tropical cyclone characteristics and natural or human-induced climate changes is a major challenge. Historical tropical cyclone records are known to be heterogeneous due to changing observing technology and reporting protocols (e.g., Landsea et al, 2004) and because data quality and reporting protocols vary substantially between regions (Knapp and Kruk, 2010). The homogeneity of the global record of tropical cyclone intensity derived from satellite data has been improved (Knapp and Kossin, 2007; Kossin et al, 2007), but these records represent only the past 30-40 years. Statistically significant trends have not been observed in records of the global annual frequency of tropical cyclones (e.g., Webster et al, 2005). Century-scale trends in frequency have been identified in the North Atlantic, but are contested (see below). Increasing century-scale frequency trends have not been identified in other basins although a declining trend in the frequency of land-falling tropical cyclones has recently been identified in a new long-term dataset for eastern Australia (Callaghan and Power, 2011). Power dissipation has increased sharply in the North Atlantic and more weakly in the western North Pacific over the past 25 years (Emanuel, 2007), but the interpretation of longer-term trends is constrained by data quality concerns as well as uncertainties on the potential role of natural climate variability in the observed increases. Satellite-based records of extreme precipitation associated with tropical cyclones also appear to have substantial homogeneity issues due to satellite changes (Lau et al. 2008). It remains difficult to robustly place tropical cyclone metrics for recent decades into a longer historical context (Knutson et al, 2010) because pre-satellite records are incomplete and therefore require the use of methods to estimate storm undercounts and other biases; these methods have provided mixed conclusions to date (e.g., for the North Atlantic basin, see Holland and Webster, 2007; Landsea, 2007; Mann et al, 2007; ; Vecchi and Knutson 2008; Landsea et al. 2009; Knutson et al, 2010; see also Figure 6).
Directory: archive -> jhurrell -> Springer archive -> In this issue archive -> United states archive -> - archive -> The Tropical Rainfall Potential (TRaP) Technique. Part 1: Description and Examples Abstract archive -> United states jhurrell -> Prediction from Weeks to Decades Springer -> Understanding and Predicting Climate Variability and Change at Monsoon Regions jhurrell -> Building Adaptive Capacity to Climate Change in Less Developed Countries Springer -> Prediction from Weeks to Decades Download 2.54 Mb. Share with your friends:
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