About 30 years of measurements made by the rain gauges located in Piedmont (Italy) have been analyzed. Rain gauges have been divided into 4 datasets considering the complex orography near Turin, namely the flatlands, ...About 30 years of measurements made by the rain gauges located in Piedmont (Italy) have been analyzed. Rain gauges have been divided into 4 datasets considering the complex orography near Turin, namely the flatlands, mountains, hills and urban areas. For each group of gauges, the Generalized Extreme Values (GEV) distributions are estimated considering both the entire dataset of available data and different sets of 3 years of data in running mode. It is shown that the GEV estimated parameters temporal series for the 3 years dataset do not present any specific trend over the entire period. The study presented here is preliminary to a future extreme rainfall event analysis using high temporal and spatial resolution X-band weather radar with a limited temporal availability of radar maps covering the same area.展开更多
One of the more critical issues in a changing climate is the behavior of extreme weather events, such as severe tornadic storms as seen recently in Moore and El Reno, Oklahoma. It is generally thought that such events...One of the more critical issues in a changing climate is the behavior of extreme weather events, such as severe tornadic storms as seen recently in Moore and El Reno, Oklahoma. It is generally thought that such events would increase under a changing climate. How to evaluate this extreme behavior is a topic currently under much debate and investigation. One approach is to look at the behavior of large scale indicators of severe weather. The use of the generalized extreme value distribution for annual maxima is explored for a combination product of convective available potential energy and wind shear. Results from this initial study show successful modeling and high quantile prediction using extreme value methods. Predicted large scale values are consistent across different extreme value modeling frameworks, and a general increase over time in predicted values is indicated. A case study utilizing this methodology considers the large scale atmospheric indicators for the region of Moore, Oklahoma for Class EF5 tornadoes on May 3, 1999 and more recently on May 20, 2013, and for the class EF5 storm in El Reno, Oklahoma on May 31, 2013.展开更多
文摘About 30 years of measurements made by the rain gauges located in Piedmont (Italy) have been analyzed. Rain gauges have been divided into 4 datasets considering the complex orography near Turin, namely the flatlands, mountains, hills and urban areas. For each group of gauges, the Generalized Extreme Values (GEV) distributions are estimated considering both the entire dataset of available data and different sets of 3 years of data in running mode. It is shown that the GEV estimated parameters temporal series for the 3 years dataset do not present any specific trend over the entire period. The study presented here is preliminary to a future extreme rainfall event analysis using high temporal and spatial resolution X-band weather radar with a limited temporal availability of radar maps covering the same area.
文摘One of the more critical issues in a changing climate is the behavior of extreme weather events, such as severe tornadic storms as seen recently in Moore and El Reno, Oklahoma. It is generally thought that such events would increase under a changing climate. How to evaluate this extreme behavior is a topic currently under much debate and investigation. One approach is to look at the behavior of large scale indicators of severe weather. The use of the generalized extreme value distribution for annual maxima is explored for a combination product of convective available potential energy and wind shear. Results from this initial study show successful modeling and high quantile prediction using extreme value methods. Predicted large scale values are consistent across different extreme value modeling frameworks, and a general increase over time in predicted values is indicated. A case study utilizing this methodology considers the large scale atmospheric indicators for the region of Moore, Oklahoma for Class EF5 tornadoes on May 3, 1999 and more recently on May 20, 2013, and for the class EF5 storm in El Reno, Oklahoma on May 31, 2013.
