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Intense precipitation events (IPE; 99th percentile) in the southeastern United States from 1950 to 2016 were analysed temporally, spatially, and synoptically. The study area was partitioned into latitudinal and physiographic regions to identify subregions that experienced significant changes in IPE frequency or intensity. Furthermore, the spatial synoptic classification (SSC) was used to ascertain what surface weather types are associated with IPEs. Additionally, in conjunction with the SSC, surface forcing mechanisms for the 30 most extreme subregional IPEs were studied to uncover the surface synoptic conditions responsible for IPEs. Results revealed that IPEs increased in frequency and intensity on an annual basis for the southeastern United States. Seasonal results indicated that IPE frequency only increased in the fall. Subregional results reveal that latitudinally, IPEs became more common in the northern latitudes of the study area, while physiographically, significant increases in IPE frequency were most pronounced in areas inland from the Atlantic Coastal Plain. An increase in the annual number of IPEs associated with moist tropical (MT) days was identified across the study area, but was more prevalent in the central and north central latitudinal regions, and areas inland from the Atlantic Coastal Plain outside of the Appalachian Mountains. This MT increase was possibly caused by more common northwards and inland intrusion of these types of IPEs. While moist moderate (MM) and transitional (TR) days were most commonly associated with IPEs, these weather types did not have significant trends. The surface forcing mechanisms most commonly associated with the strongest IPEs were tropical events, followed by stationary fronts and concentric low‐pressure systems.
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A maximum entropy approach to defining geographic bounds on growth and yield model usage
Growth and yield models are essential tools in modern forestry, especially for intensively managed loblolly pine plantations in the southeastern United States. While model developers often have a good idea of where these models should be used with respect to geographic location, determining geographic bounds for model usage can be daunting. Such bounds provide suitable areas where model predictions are likely to behave as expected or identify areas where models may do a poor job of characterizing the growth of a resource. In this research, we adapted a niche model methodology, commonly used to identify suitable spots for species occurrence (maximum entropy), to identify areas for using growth and yield models built from plots established in the Lower Coastal Plain and Piedmont/Upper Coastal Plain in the southeastern United States. The results from this analysis identify areas with similar climatic envelopes and soil properties to the areas where data was collected to fit these growth and yield models. These areas show notable overlap with the areas prescribed for use by the evaluated growth and yield models and support practitioners use of these models throughout these regions. Furthermore, this methodology can be applied to different forest models built using large regional extents as long as climatic and soil values are available for each site.
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- Award ID(s):
- 1916720
- PAR ID:
- 10507735
- Publisher / Repository:
- Frontiers in Forests and Global Change
- Date Published:
- Journal Name:
- Frontiers in Forests and Global Change
- Volume:
- 6
- ISSN:
- 2624-893X
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.3389/ffgc.2023.1215713
