Coupled spatiotemporal variability of temperature and spring phenology in the Eastern United States

2015 ◽  
Vol 36 (4) ◽  
pp. 1744-1754 ◽  
Author(s):  
Liang Liang ◽  
Xiaoyang Zhang
Keyword(s):  
United States ◽  
Spatiotemporal Variability ◽  
Eastern United States ◽  
Spring Phenology

scholarly journals Spatiotemporal Variability of Tropical Cyclone Precipitation Using a High-Resolution, Gridded (0.25° × 0.25°) Dataset for the Eastern United States, 1948–2015

2020 ◽  
Vol 33 (5) ◽  
pp. 1803-1819 ◽  
Author(s):  
Joshua C. Bregy ◽  
Justin T. Maxwell ◽  
Scott M. Robeson ◽  
Jason T. Ortegren ◽  
Peter T. Soulé ◽  
...  
Keyword(s):  
United States ◽  
Tropical Cyclone ◽  
Large Scale ◽  
Southern Oscillation ◽  
Spatiotemporal Variability ◽  
Eastern United States ◽  
Percentage Contribution ◽  
Rain Gauges ◽  
The North ◽  
Climate Interactions

AbstractTropical cyclones (TCs) are an important source of precipitation for much of the eastern United States. However, our understanding of the spatiotemporal variability of tropical cyclone precipitation (TCP) and the connections to large-scale atmospheric circulation is limited by irregularly distributed rain gauges and short records of satellite measurements. To address this, we developed a new gridded (0.25° × 0.25°) publicly available dataset of TCP (1948–2015; Tropical Cyclone Precipitation Dataset, or TCPDat) using TC tracks to identify TCP within an existing gridded precipitation dataset. TCPDat was used to characterize total June–November TCP and percentage contribution to total June–November precipitation. TCP totals and contributions had maxima on the Louisiana, North Carolina, and Texas coasts, substantially decreasing farther inland at rates of approximately 6.2–6.7 mm km−1. Few statistically significant trends were discovered in either TCP totals or percentage contribution. TCP is positively related to an index of the position and strength of the western flank of the North Atlantic subtropical high (NASH), with the strongest correlations concentrated in the southeastern United States. Weaker inverse correlations between TCP and El Niño–Southern Oscillation are seen throughout the study site. Ultimately, spatial variations of TCP are more closely linked to variations in the NASH flank position or strength than to the ENSO index. The TCP dataset developed in this study is an important step in understanding hurricane–climate interactions and the impacts of TCs on communities, water resources, and ecosystems in the eastern United States.

scholarly journals Multiscale modeling of spring phenology across Deciduous Forests in the Eastern United States

2016 ◽  
Vol 22 (2) ◽  
pp. 792-805 ◽  
Author(s):  
Eli K. Melaas ◽  
Mark A. Friedl ◽  
Andrew D. Richardson
Keyword(s):  
United States ◽  
Multiscale Modeling ◽  
Deciduous Forests ◽  
Eastern United States ◽  
Spring Phenology

scholarly journals Spatiotemporal Variability of Hourly Precipitation over the Eastern Contiguous United States from Stage IV Multisensor Analyses

2008 ◽  
Vol 9 (1) ◽  
pp. 3-21 ◽  
Author(s):  
Ana L. Kursinski ◽  
Steven L. Mullen
Keyword(s):  
United States ◽  
Numerical Models ◽  
Geometric Model ◽  
Stage Iv ◽  
Spatiotemporal Variability ◽  
Eastern United States ◽  
Hourly Precipitation ◽  
Prediction Systems ◽  
Decorrelation Estimates

Abstract The statistical character of precipitation events from hourly stage IV analyses is documented for the eastern United States during the cool [December–February (DJF)] and the warm [June–August (JJA)] seasons for the four years of 2002–05. Isotropic e-folding distances and in situ e-folding times are computed for mesh sizes that vary from 4 km (the minimal stage IV pixel size) to 32 km for two thresholds: light (1 mm h−1) and heavy (5 mm h−1) precipitation rates. Marked seasonal variability characterizes the e-folding times. They typically run between 2 and 3 h during winter and 1 and 2 h during summer for light events, and they run an hour shorter for heavy rainfall during both seasons. Spatial decorrelation estimates also reveal considerable seasonal and geographical variability; e-folding distances typically lie between 60 and 180 km during the winter and between 30 and 60 km during the summer for light episodes, and they are approximately a factor of 2 to 3 shorter for heavy events. Anisotropic statistics are estimated by a simple geometric model. Hourly precipitation patterns show a preference for a southwest–northeast orientation during both seasons with greater elongation during the winter. Mean propagation velocities of precipitating systems are faster and are more closely aligned with the dilatation axis during the winter. These statistics should provide useful guidance for diagnosing and improving the spatiotemporal variance characteristics of precipitation for downscaling algorithms and numerical models of hydrometeorological prediction systems.

Sign in / Sign up

Export Citation Format

Share Document