Suchergebnisse

Climatology is an area with many applications of extreme–value theory. In applications to climatic data it is necessary to consider the distribution ol extremes for dependent random variables and to make allowance for non–stationarity (seasonal variation). It is shown that also for such data the classical limiting distributions for normalized maxima of independent and identically distributed random variables remain useful candidates to describe the distribution of the largest value in a year.Parameter estimation of extreme–value distributions is briefly reviewed. Attention is paid to variance–reduction of quantile estimates by making use of more observations than just the annual maxima. Three examples of applications deal with topics like the estimation of large quantiles by combining information from several records in a region, shifts in the distribution of maxima due to changes in measurement practices, and the use of covariates.

Abstract. Derechos are high-impact convective wind events that can cause fatalities and widespread losses. In this study, 40 derechos affecting Germany between 1997 and 2014 are analyzed to estimate the derecho risk. Similar to the United States, Germany is affected by two derecho types. The first, called warm-season-type derechos, form in strong southwesterly 500 hPa flow downstream of western European troughs and account for 22 of the 40 derechos. They have a peak occurrence in June and July. Warm-season-type derechos frequently start in the afternoon and move either eastward along the Alpine forelands or northeastward across southern central Germany. Associated proximity soundings indicate strong 0–6 and 0–3 km vertical wind shear and a median of mixed-layer convective available potential energy (mixed-layer CAPE) around 500 J kg−1. The second derecho type, the cold-season-type derecho, forms in strong northwesterly 500 hPa flow, frequently in association with mid-tropospheric potential vorticity (PV) intrusions, and accounts for 18 of the 40 derechos. They are associated with a secondary peak from December to February. Cold-season-type derechos start over or close to the North Sea and primarily affect northern and central Germany; their start time is not strongly related to the peak of diurnal heating. Proximity soundings indicate high-shear–low-CAPE environments. A total of 15 warm-season-type and 9 cold-season-type derechos had wind gusts reaching 33 m s−1 in at least three locations. Although warm-season derechos are more frequent, the path length of cold-season-type derechos is on average 1.4 times longer. Thus, these two types of German derechos are likely to have similar impacts.

AbstractResidents of the Oklahoma City metropolitan area are frequently threatened by tornadoes. Previous research indicates that perceptions of tornado threat affect behavioral choices when severe weather threatens, and as such are important to study. In this paper, we examine the potential influence of tornado climatology on risk perception. Residents across central Oklahoma were surveyed about their perceptions of tornado proneness for their home location, and this was compared to the local tornado climatology. Mapping and programming tools were then used to identify relationships between respondents' perceptions and actual tornado events. Research found that some dimensions of the climatology, such as tornado frequency, nearness, and intensity have complex effects on risk perception. In particular, tornadoes that were intense, close, and recent had the strongest positive influence on risk perception, but weaker tornadoes appeared to produce an "inoculating" effect. Additional factors were influential, including sharp spatial discontinuities between neighboring places that were not tied to any obvious physical feature or the tornado climatology. Respondents holding lower perceptions of risk also reported lower rates of intention to prepare during tornado watches. By studying place-based perceptions, this research aims to provide a scientific basis for improved communication efforts before and during tornado events, and for identifying vulnerable populations.

Auf dem Hintergrund der Bedeutung der historischen Klimatologie für das Verständnis klimatischer Prozesse und der Interaktion zwischen Mensch und Umwelt, gibt der Beitrag einen Überblick über Daten und angewandte Methoden in der historischen Klimakunde. Es werden drei wesentliche Gruppen unterschieden, deskriptive Wetterdaten, Daten aus dem Ablesen von Instrumenten und proxy-Daten, sowie die verschiedenen Methoden, Informationen aus diesen Daten zu gewinnen, vorgestellt. Dabei rangiert die angewandte Methodik der Klimakunde von der Anwendung historischer kritischer Quellenanalysen über hermeneutische Verfahren bis hin zu numerischen naturwissenschaftlichen und statistischen Vorgehensweisen. (ICH)

Abstract. A new approach was recently proposed to compute climatological statistical sensitivities. It was applied on an already available classification of Mediterranean intense cyclones. However, those sensitivity results are questionable due to the limited homogeneity of some cyclone classes, which severely hampers the application of the statistical sensitivity analysis technique. In this study, a new classification of Mediterranean intense cyclones is built with the aim of improving the reliability of the final climatological sensitivity results. In addition to implementing a regional classification and a subsequent division according to the preceding conditions that lead to cyclone formation, a cluster pruning is applied to maximize the homogeneity of the classes. The increased cluster homogeneity and the higher significance of the obtained sensitivity estimates are quantified. Furthermore, the improved representativeness of the sensitivity fields derived after cluster pruning is tested and compared to previous results by means of numerical experiments. Eventually, summary sensitivity fields highlight the European Atlantic coasts, central and western Europe, the central and western Mediterranean basin and north african lands as sensitive regions for the evolution of these Mediterranean high-impact systems. Although some outstanding improvements are confirmed in this study, a further verification experiments are needed to objectively verify the sensitivity results and build solid confidence on the method.

Abstract. This study is focused on the modification of a typhoon rainfall climatological model, by using the dataset up to 2006 and including data collected from rain gauge stations established after the 921 earthquake (1999). Subsequently, the climatology rainfall models for westward- and northward-moving typhoons are established by using the typhoon track classification from the Central Weather Bureau. These models are also evaluated and examined using dependent cases collected between 1989 and 2006 and independent cases collected from 2007 to 2011. For the dependent cases, the average total rainfall at all rain gauge stations forecasted using the climatology rainfall models for westward- (W-TRCM12) and northward-moving (N-TRCM12) typhoons is superior to that obtained using the original climatological model (TRCM06). Model W-TRCM12 significantly improves the precipitation underestimation of model TRCM06. The independent cases show that model W-TRCM12 provides better accumulated rainfall forecasts and distributions than model TRCM06. A climatological model for accompanied northeastern monsoons (A-TRCM12) for special typhoon types has also been established. The current A-TRCM12 model only contains five historical cases and various typhoon combinations can cause precipitation in different regions. Therefore, precipitation is likely to be significantly overestimated and high false alarm ratios are likely to occur in specific regions. For example, model A-TRCM12 significantly overestimates the rainfall forecast for Typhoon Mitag, an independent case from 2007. However, it has a higher probability of detection than model TRCM06. From a disaster prevention perspective, a high probability of detection is much more important than a high false alarm ratio. The modified models can contribute significantly to operational forecast.

Abstract. The World Wide Lightning Location Network (WWLLN) data have been used to perform a lightning climatology in the South-West Indian Ocean (SWIO) region from 2005 to 2011. Maxima of lightning activity were found in the Maritime Continent and southwest of Sri Lanka (>50 fl km−2 yr−1) but also over Madagascar and above the Great Lakes of East Africa (>10–20 fl km−2 yr−1). Lightning flashes within tropical storms and tropical cyclones represent 50 % to 100 % of the total lightning activity in some oceanic areas of the SWIO (between 10° S and 20° S). The SWIO is characterized by a wet season (November to April) and a dry season (May to October). As one could expect, lightning activity is more intense during the wet season as the Inter Tropical Convergence Zone (ITCZ) is present over all the basin. Flash density is higher over land in November–December–January with values reaching 3–4 fl km−2 yr−1 over Madagascar. During the dry season, lightning activity is quite rare between 10° S and 25° S. The Mascarene anticyclone has more influence on the SWIO resulting in shallower convection. Lightning activity is concentrated over ocean, east of South Africa and Madagascar. A statistical analysis has shown that El Niño–Southern Oscillation mainly modulates the lightning activity up to 56.8% in the SWIO. The Indian Ocean Dipole has a significant contribution since ~49% of the variability is explained by this forcing in some regions. The Madden–Julian Oscillation did not show significative impact on the lightning activity in our study.