Developments in synoptic climatology in the 1990s included advances in traditional synoptic climatology, empirical downscaling, and dynamical downscaling (i.e. regional climate modelling). The research emphasis in traditional, empirical-statistical approaches to synoptic climatology shifted from methodological development to applications of widely accepted classification techniques, including manual, correlation-based, eigenvector-based, compositing and indexing schemes. In contrast, most efforts in empirical downscaling, which became a well-established field of synoptic climatology during the 1990s, were directed to model development; applications were of secondary concern. Similarly, regional climate models (RCMs) burst onto the scene during the decade and focused on model development, although important progress was made in linking or coupling RCMs to regional or local surface climate systems. This paper discusses prospects for the future of traditional synoptic climatology, empirical downscaling and regional climate modelling. It concludes by looking at the present role of geographic information system (GIS) concepts in synoptic climatology and the potential future role of GIS to the field.

No abstract

Manual and correlation‐based (also known as Lund or Kirchhofer) classifications are important to synoptic climatology, but both have significant drawbacks. Manual classifications are inherently subjective and labour intensive, whereas correlation‐based classifications give the investigator little control over the map‐patterns generated by the computer. This paper develops a simple procedure that combines these two classification methods, thereby minimizing these weaknesses. The hybrid procedure utilizes a relatively short‐term manual classification to generate composite pressure surfaces, which are then used as seeds in a long‐term correlation‐based computer classification. Overall, the results show that the hybrid classification reproduces the manual classification while optimizing speed, objectivity and investigator control, thus suggesting that the hybrid procedure is superior to the manual or correlation classifications as they are currently used. More specifically, the results demonstrate little difference between the hybrid procedure and the original manual classification at monthly and longer time‐scales, with less internal variation in the hybrid types than in the subjective categories. However, the two classifications showed substantial differences at the daily level, not because of poor performance by the hybrid procedure, but because of errors introduced by the subjectivity of the manual classification. © 1997 Royal Meteorological Society. Int.J.Climatol., Vol.17, 1381‐1396 (No. of Figures: 9 No. of Tables: 1 No. of References: 30)

Manual and correlation-based (also known as Lund or Kirchhofer) classi®cations are important to synoptic climatology, but both have signi®cant drawbacks. Manual classi®cations are inherently subjective and labour intensive, whereas correlationbased classi®cations give the investigator little control over the map-patterns generated by the computer. This paper develops a simple procedure that combines these two classi®cation methods, thereby minimizing these weaknesses. The hybrid procedure utilizes a relatively short-term manual classi®cation to generate composite pressure surfaces, which are then used as seeds in a long-term correlation-based computer classi®cation. Overall, the results show that the hybrid classi®cation reproduces the manual classi®cation while optimizing speed, objectivity and investigator control, thus suggesting that the hybrid procedure is superior to the manual or correlation classi®cations as they are currently used. More speci®cally, the results demonstrate little difference between the hybrid procedure and the original manual classi®cation at monthly and longer timescales , with less internal variation in the hybrid types than in the subjective categories. However, the two classi®cations showed substantial differences at the daily level, not because of poor performance by the hybrid procedure, but because of errors introduced by the subjectivity of the manual classi®cation.

No abstract

The meteorology flood hydroclimatolog and socioeconomic impacts of the Flood of January 1996 in the Susquehanna River Basin are explored. The analysis explains how an unusual storm system brought high humidities, high temperatures, strong winds, and heavy rain to the basin. The rapid melt of the deep snowpack, combined with the heavy rainfall, produced the sudden release of large volumes of water. Because the ground surface was frozen or saturated, this water moved primarily as overland flow. Thus, the flood waters were not restricted to areas immediately adjacent to stream channels and, consequently, some of the largest impacts were on people, property, and infrastructure in areas not normally prone to flooding. Socioeconomic patterns of flooding over time and space are investigated to put this flood into context and to highlight its impacts. The analysis concludes that if such overland flooding is a more common feature of climate change, then the current vulnerability to this form of flooding and its economic implications must be considered carefully.

No abstract

No abstract