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 (Z^*), column-averaged potential vorticity anomaly (PV^*), 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, PV^* and Z^* blocked regions often have higher pattern correlation and spatial similarity, though these two methods also display high agreement with AGP in some instances.Z^* finds the largest (and greatest number of) blocked regions, while PV^*-detected regions are smallest in all instances except Southern Hemisphere winter. In some cases, PV^* 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.
Highlights
Atmospheric blocking is a synoptic-scale weather phenomenon with important social and ecological impacts that arise due to its correlation with many kinds of extreme weather, such as heat waves (Pfahl and Wernli 2012; Grotjahn 2011; Lee and Grotjahn 2015), cold spells (Sillmann et al 2011; Grotjahn and Faure 2008), and floods (Houze et al 2011; Hong et al 2011)
Our analysis shows that each of the assessed algorithms only capture a subset of meteorological patterns defined by the American Meteorological Society (AMS) definition of blocking, and the level of agreement between algorithms is highly dependent on region and block type
In order to explore some of the points raised by Davini et al (2012) and Scherrer et al (2006)— the differences due to variable choice and region—we utilize schemes that are based on two different variables (Z500 and vertically averaged PV (VPV)) and field types
Summary
Atmospheric blocking is a synoptic-scale weather phenomenon with important social and ecological impacts that arise due to its correlation with many kinds of extreme weather, such as heat waves (Pfahl and Wernli 2012; Grotjahn 2011; Lee and Grotjahn 2015), cold spells (Sillmann et al 2011; Grotjahn and Faure 2008), and floods (Houze et al 2011; Hong et al 2011). The analysis, which was performed on 43 years of Northern Hemisphere data, concludes that these methods yield similar results in terms of calculated blocking frequency and duration across the time and longitude axes These are only two possible metrics under which objective methods can be examined, and other papers have noted inherent differences in the methods due to both the data and the chosen method. Our analysis shows that each of the assessed algorithms only capture a subset of meteorological patterns defined by the AMS definition of blocking, and the level of agreement between algorithms is highly dependent on region and block type This an important point to consider when attempting to assess current and future blocking trends and the impacts of corresponding extreme weather.
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