Toward a Multi-Decadal Climatology of North Pacific Polar Lows Employing Dynamical Downscaling

Chen, Fei; Geyer, Beate; Zahn, Matthias; Storch, Hans von

doi:10.3319/tao.2011.11.02.01(a)

Cited by 8 publications

(10 citation statements)

References 27 publications

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“…Various authors have demonstrated that Polar Lows and other mesoscale windstorms can be described by high-resolution numerical models, such as Fu et al and Yanase et el. in Japan Sea [8][9][10]; Bresch et al in Bering Sea [11]; Businger and Blier in Gulf of Alaska [2,12]; Chen et al in North Pacific [13]; Cavicchia and von Storch for "medicanes" in the Mediterranean Sea [14]; and Zahn and von Storch in North Atlantic [7]. Dynamical mechanisms and synoptic conditions of Polar Low formation as well as life cycles have been discussed in various case studies.…”

Section: Introductionmentioning

confidence: 99%

Trends and Variability of North Pacific Polar Lows

Chen¹,

Storch²

2013

Advances in Meteorology

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The 6-hourly 1948–2010 NCEP 1 reanalyses have been dynamically downscaled for the region of the North Pacific. With a detecting-and-tracking algorithm, the climatology of North Pacific Polar Lows has been constructed. This derived climatology is consistent with the limited observational evidence in terms of frequency and spatial distribution. The climatology exhibits strong year-to-year variability but weak decadal variability and a small positive trend. A canonical correlation analysis describes the conditioning of the formation of Polar Lows by characteristic seasonal mean flow regimes, which favor, or limit, cold air outbreaks and upper air troughs.

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Section: Introductionmentioning

confidence: 99%

Trends and Variability of North Pacific Polar Lows

Chen¹,

Storch²

2013

Advances in Meteorology

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“…Livezey (1995) described some standard procedures for determining the skill of weather forecast methods. A number of studies have identified enhanced variability at medium scales and more realistic spatial detail, not only of physiographic effects (e.g., coasts) but also of dynamical processes, such as polar lows, typhoons, or medicanes (Mediterranean tropical-like cyclones), as values added by downscaling (Zahn et al 2008;Chen et al 2012;Cavicchia and von Storch 2012;Feser et al 2011;Di Luca et al 2011).…”

Section: Remaining Issues With Dynamical Downscalingmentioning

confidence: 99%

Reconsidering the Quality and Utility of Downscaling

Takayabu¹,

Kanamaru

Dairaku

et al. 2016

Journal of the Meteorological Society of Japan

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Dynamical downscaling (DDS) is performed using regional climate models (RCMs) with global atmospheric states as the input, but there is no consensus among researchers on how to define and estimate the resolvable scale of the various climatic variables obtained by DDS. Sources of RCM uncertainties, including both internal model and intermodel variability, have been assessed by performing ensemble simulations and model intercomparisons, sometimes under the controversial assumption that model bias is independent of the climatic state. Compared with low-resolution global climate simulations, DDS can add value in several ways. For example, because they consider high-resolution topographic data, RCMs can often capture mesoscale phenomena and can better represent climate dynamics. Another downscaling method, empirical statistical downscaling (ESD), is complementary to DDS because it is based on a different philosophy (i.e., sources of information) and on a mostly different set of assumptions. More collaboration and communication should be encouraged among those who develop models, those who use models and perform downscaling, those who use downscaling data, and those who make decisions

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“…To do so, a regional climate model was conditioned by large-scale information of 28 NCEP re-analyses. It turned out that in this way the formation and life cycles of Polar Lows during 29 the past decades could be reconstructed homogeneously without exploiting sub-synoptic 30 information in initial fields (Chen et al 2012). 31…”

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confidence: 99%