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Sökning: id:"swepub:oai:DiVA.org:su-208767" > Dynamics and predic...

Dynamics and predictability of cold spells over the Eastern Mediterranean

Hochman, A. (författare)
Karlsruhe Inst Technol, Inst Meteorol & Climate Res, Dept Tropospher Res, Karlsruhe, Germany.
Scher, Sebastian, 1990- (författare)
Stockholms universitet,Meteorologiska institutionen (MISU),Stockholm Univ, Dept Meteorol, Stockholm, Sweden.;Stockholm Univ, Bolin Ctr Climate Res, Stockholm, Sweden.
Quinting, J. (författare)
Karlsruhe Inst Technol, Inst Meteorol & Climate Res, Dept Tropospher Res, Karlsruhe, Germany.
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Pinto, J. G. (författare)
Karlsruhe Inst Technol, Inst Meteorol & Climate Res, Dept Tropospher Res, Karlsruhe, Germany.
Messori, Gabriele (författare)
Uppsala universitet,Stockholms universitet,Meteorologiska institutionen (MISU),Uppsala University, Sweden; Centre of Natural Hazards and Disaster Science (CNDS), Sweden,Luft-, vatten- och landskapslära,Stockholm Univ, Dept Meteorol, Stockholm, Sweden.;Stockholm Univ, Bolin Ctr Climate Res, Stockholm, Sweden.
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Karlsruhe Inst Technol, Inst Meteorol & Climate Res, Dept Tropospher Res, Karlsruhe, Germany Meteorologiska institutionen (MISU) (creator_code:org_t)
2020-10-10
2022
Engelska.
Ingår i: Climate Dynamics. - : Springer Science and Business Media LLC. - 0930-7575 .- 1432-0894. ; 58:7-8, s. 2047-2064
  • Tidskriftsartikel (refereegranskat)
Abstract Ämnesord
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  • The accurate prediction of extreme weather events is an important and challenging task, and has typically relied on numerical simulations of the atmosphere. Here, we combine insights from numerical forecasts with recent developments in dynamical systems theory, which describe atmospheric states in terms of their persistence (θ−1) and local dimension (d), and inform on how the atmosphere evolves to and from a given state of interest. These metrics are intuitively linked to the intrinsic predictability of the atmosphere: a highly persistent, low-dimensional state will be more predictable than a low-persistence, high-dimensional one. We argue that θ−1 and d, derived from reanalysis sea level pressure (SLP) and geopotential height (Z500) fields, can provide complementary predictive information for mid-latitude extreme weather events. Specifically, signatures of regional extreme weather events might be reflected in the dynamical systems metrics, even when the actual extreme is not well-simulated in numerical forecasting systems. We focus on cold spells in the Eastern Mediterranean, and particularly those associated with snow cover in Jerusalem. These rare events are systematically associated with Cyprus Lows, which are the dominant rain-bearing weather system in the region. In our analysis, we compare the ‘cold spell Cyprus Lows’ to other ‘regular’ Cyprus Low days. Significant differences are found between cold spells and ‘regular’ Cyprus Lows from a dynamical systems perspective. When considering SLP, the intrinsic predictability of cold spells is lowest hours before the onset of snow. We find that the cyclone’s location, depth and magnitude of air-sea fluxes play an important role in determining its intrinsic predictability. The dynamical systems metrics computed on Z500 display a different temporal evolution to their SLP counterparts, highlighting the different characteristics of the atmospheric flow at the different levels. We conclude that the dynamical systems approach, although sometimes challenging to interpret, can complement conventional numerical forecasts and forecast skill measures, such as model spread and absolute error. This methodology outlines an important avenue for future research, which can potentially be fruitfully applied to other regions and other types of weather extremes.

Ämnesord

NATURVETENSKAP  -- Geovetenskap och miljövetenskap (hsv//swe)
NATURAL SCIENCES  -- Earth and Related Environmental Sciences (hsv//eng)
NATURVETENSKAP  -- Geovetenskap och miljövetenskap -- Meteorologi och atmosfärforskning (hsv//swe)
NATURAL SCIENCES  -- Earth and Related Environmental Sciences -- Meteorology and Atmospheric Sciences (hsv//eng)

Nyckelord

Atmospheric dynamics
Chaos
Dynamical systems
Extreme temperatures
Extreme weather
Numerical weather prediction
Prediction
Weather forecasting

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