Twentieth century North Atlantic jet variability

Woollings, Tim; Czuchnicki, Camelia; Franzke, Christian

doi:10.1002/qj.2197

Cited by 86 publications

(114 citation statements)

References 47 publications

(48 reference statements)

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“…The simulations for the UT/LS region have their largest AHTDs in the northern midlatitudes with 95 to 177 km. These errors are caused by the north-south meandering of the jet (Woollings et al, 2014) and higher small-scale variability of the wind field in this region. The second largest errors of the simulations in the UT/LS region occur in the tropics with about 75 km on average followed by the Arctic and southern midlatitudes with about 50 km on average.…”

Section: Spatial and Temporal Variations Of Trajectory Errorsmentioning

confidence: 98%

Trajectory errors of different numerical integration schemes diagnosed with the MPTRAC advection module driven by ECMWF operational analyses

Rößler

Stein²,

Heng

et al. 2018

Geosci. Model Dev.

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Abstract. The accuracy of trajectory calculations performed by Lagrangian particle dispersion models (LPDMs) depends on various factors. The optimization of numerical integration schemes used to solve the trajectory equation helps to maximize the computational efficiency of large-scale LPDM simulations. We analyzed global truncation errors of six explicit integration schemes of the Runge-Kutta family, which we implemented in the Massive-Parallel Trajectory Calculations (MPTRAC) advection module. The simulations were driven by wind fields from operational analysis and forecasts of the European Centre for Medium-Range Weather Forecasts (ECMWF) at T1279L137 spatial resolution and 3 h temporal sampling. We defined separate test cases for 15 distinct regions of the atmosphere, covering the polar regions, the midlatitudes, and the tropics in the free troposphere, in the upper troposphere and lower stratosphere (UT/LS) region, and in the middle stratosphere. In total, more than 5000 different transport simulations were performed, covering the months of January, April, July, and October for the years 2014 and 2015. We quantified the accuracy of the trajectories by calculating transport deviations with respect to reference simulations using a fourth-order Runge-Kutta integration scheme with a sufficiently fine time step. Transport deviations were assessed with respect to error limits based on turbulent diffusion. Independent of the numerical scheme, the global truncation errors vary significantly between the different regions. Horizontal transport deviations in the stratosphere are typically an order of magnitude smaller compared with the free troposphere. We found that the truncation errors of the six numerical schemes fall into three distinct groups, which mostly depend on the numerical order of the scheme. Schemes of the same order differ little in accuracy, but some methods need less computational time, which gives them an advantage in efficiency. The selection of the integration scheme and the appropriate time step should possibly take into account the typical altitude ranges as well as the total length of the simulations to achieve the most efficient simulations. However, trying to summarize, we recommend the third-order Runge-Kutta method with a time step of 170 s or the midpoint scheme with a time step of 100 s for efficient simulations of up to 10 days of simulation time for the specific ECMWF high-resolution data set considered in this study. Purely stratospheric simulations can use significantly larger time steps of 800 and 1100 s for the midpoint scheme and the third-order Runge-Kutta method, respectively.

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Section: Spatial and Temporal Variations Of Trajectory Errorsmentioning

confidence: 98%

Trajectory errors of different numerical integration schemes diagnosed with the MPTRAC advection module driven by ECMWF operational analyses

Rößler

Stein²,

Heng

et al. 2018

Geosci. Model Dev.

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“…Since the storm-tracks are associated with the position of the jet stream in the middle troposphere, and the number of cyclones -with jet intensity [10,17], it is obvious that the jet streams are the most important factor for climate formation. Let us consider the impact of two major climate signals (the NAO and EAO) on the jet stream parameters.…”

Section: Methodsmentioning

confidence: 99%

“…Let us consider the impact of two major climate signals (the NAO and EAO) on the jet stream parameters. According [17] in winter the jet stream over the North Atlantic is most often located in three latitudinal bands: 34 -38°N, 42 -46°N and 54 -58°N (Fig. 7, b).…”

Section: Methodsmentioning

confidence: 99%

“…In contrast to the EAO, the NAO partially controls the jet stream velocity when the jet is in the northern and central positions. [17] Anomalies of the zonal wind at 500 hPa indicate the EAO to serve a "switch" of the jet stream position over the Atlantics. In winter, in the positive EAO phase the anomalous cyclonic circulation appears over the North Atlantic (Fig.…”

Section: Methodsmentioning

confidence: 99%

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The East Atlantic Oscillation: Mechanism and Impact on the European Climate in Winter

Mikhailova¹,

Yurovsky²

2016

PhO

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The second leading mode of principal component analysis of the winter atmospheric pressure pattern in the North Atlantic-European region known as the East Atlantic Oscillation (EAO) is considered. The winter EAO pattern exhibits well-defined dipole at 500-hPa geopotential height (H 500 ) with centers over the North Atlantic and the Central Europe. The EAO phase-to-phase shifts reflect the general atmospheric circulation changes and the zonal (meridional) circulation dominates in positive (negative) EAO phase. This induces storm tracks spatial shift, heat and moisture transport redistribution, which in turn results in anomalous winter air temperature and precipitation in the Europe. The surface air temperature and precipitation interannual variability explained by EAO index is 25 -35 % and 15 -25 %, respectively. Positive EAO phase is associated with the higher winter air temperatures in Europe (mean anomalies are from +0.3 to +3.5 °C), and negative EAO phase is associated with the lower winter air temperatures (mean anomalies are from -1.5 to -0.5 °C). Basin-wide changes in the intensity and location of the North Atlantic polar jet stream are observed between the EAO opposite phases. Anomalous cyclonic (anticyclonic) circulation over the North Atlantic and southward (northward) shift of the North Atlantic jet stream is shown to be inherent in positive (negative) EAO phase.

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“…The peak of these modes are located at 45N, 58N and 37N, respectively, all of which are within 1 • of the reanalysis estimates of jet latitude calculated over the same period. The spread in ensembles captures the observed distribution, especially given the observed tri-modal structure has a measure of decadal variability in it Woollings et al (2014). In comparison to the AMIP5 and CMIP5 jet latitude distributions (Fig.…”

Section: Jet Streammentioning

confidence: 99%

Assessing mid-latitude dynamics in extreme event attribution systems

et al. 2016

Self Cite

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tracks are too zonal over the Atlantic in the CMIP5 and AMIP5 ensembles, but better simulated in HadAM3P with the exception of being too weak over Western Europe. In all cases, the CMIP5 and AMIP5 performances were almost identical, suggesting that the biases in atmospheric modes considered here are not strongly coupled to SSTs, and perhaps other model characteristics such as resolution are more important. For event attribution studies, it is recommended that rather than taking statistics over the entire CMIP5 or AMIP5 available models, only models capable of producing the relevant dynamical phenomena be employed.

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Twentieth century North Atlantic jet variability

Cited by 86 publications

References 47 publications

Trajectory errors of different numerical integration schemes diagnosed with the MPTRAC advection module driven by ECMWF operational analyses

Trajectory errors of different numerical integration schemes diagnosed with the MPTRAC advection module driven by ECMWF operational analyses

The East Atlantic Oscillation: Mechanism and Impact on the European Climate in Winter

Assessing mid-latitude dynamics in extreme event attribution systems

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