Abstract
An increasing focus of climate change studies is the projection of storm events characterized by heavy, very heavy, extreme, and/or intense precipitation. Projected changes in the spatiotemporal distributions of such intense precipitation events remain uncertain due to large measures of variability in both the definition and evidence of increased intensity in the upper percentile range of observed daily precipitation distributions, particularly on a regional basis. As a result, projecting changes in future precipitation at the upper tail of the distribution (i.e., the heavy to heaviest events), such as through the use of stochastic weather generator programs, remains challenging. One approach to address this challenge is to better define what constitutes intense precipitation events and the degree of location-specific adjustment needed for the weather generator programs to appropriately account for potential increases in precipitation intensity due to climate change. In this study, we synthesized information on categories of intense precipitation events and assessed reported trends in the categories at national and regional scales within the context of applying this information to stochastic weather generation. Investigations of adjusting weather generation models to include long-term regional trends in intense precipitation events are limited, and modeling trends in site-specific future precipitation distributions forecasted by weather generator programs remains challenging. Probability exceedance curves and variations between simulated and observed distributions can help in modeling and assessment of trends in future extreme precipitation events that reflect changes in precipitation intensity due to climate change.
Highlights
Changes in the amount of precipitation, and the frequency and intensity of precipitation events are well-known phenomena occurring globally at multiple time scales [1,2]
The events forming the upper tails of these daily distributions, commonly known as intense precipitation events [11,12,13], are frequently the primary drivers of adverse environmental impacts and need to be analyzed comprehensively in order to fully understand the implications of changing precipitation patterns as driven by global climate change
We review the existing literature regarding definitions of intense precipitation events and changes in their distribution due to current and projected future climate change for their specific application to stochastic weather generators and their associated site-specific and management-scale questions relevant to agricultural productivity
Summary
Changes in the amount of precipitation, and the frequency and intensity of precipitation events are well-known phenomena occurring globally at multiple time scales [1,2] Changes in these precipitation characteristics can adversely impact the environment by increasing storm water management problems [3,4], soil erosion [5], and runoff [6]; and by decreasing water quality [7,8] and agricultural productivity [9]. We review the existing literature regarding definitions of intense precipitation events and changes in their distribution due to current and projected future climate change for their specific application to stochastic weather generators and their associated site-specific and management-scale questions relevant to agricultural productivity. This review will further serve as the foundation for subsequent case study analyses where approaches for adjusting forecasted precipitation distributions at a specific location can be tested and evaluated with the aim of applying such adjustments to agricultural productivity models
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