Atmospheric blocking and intercomparison of objective detection methods: flow field characteristics
- PMID: 31929689
- PMCID: PMC6936472
- DOI: 10.1007/s00382-019-04782-5
Atmospheric blocking and intercomparison of objective detection methods: flow field characteristics
Abstract
Objective methods for identifying and quantifying atmospheric blocking have been developed over recent decades, primarily targeting North Atlantic blocks. Differences arise from these methods, leading to changes in the resultant blocking climatology. To understand these differences, and better inform future assessments built on quantitative detection of blocks, this paper examines blocking properties produced by three different objective detection algorithms over the global extratropics. Blocking criteria examined include 500 hPa geopotential height anomaly ( ), column-averaged potential vorticity anomaly ( ), and 500 hPa geopotential height gradient (AGP). Results are analyzed for blocking climatologies and for instantaneous blocking patterns, as well as distributions of block size, speed, duration, and distance traveled. The results emphasize physical characteristics of the flow field and the subsequent blocking regions that emerge; overall, and blocked regions often have higher pattern correlation and spatial similarity, though these two methods also display high agreement with AGP in some instances. finds the largest (and greatest number of) blocked regions, while -detected regions are smallest in all instances except Southern Hemisphere winter. In some cases, tracks a nearby jet streak, leading to differences with height-based algorithms. All three algorithms detect some questionable low-latitude blocks that are stationary and persist but do not impair zonal flow, although at different times. Therefore, careful consideration of the algorithm biases is important in future blocking studies. For example, linking extreme weather to detected blocking could vary substantially depending on the algorithm used.
Keywords: Blocking; Climate variability; Climatology; Objective detection.
© The Author(s) 2019.
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