How I Learned to Love Normal-Mode Rossby–Haurwitz Waves

Madden, Roland A.

doi:10.1175/bams-d-17-0293.1

Cited by 10 publications

(13 citation statements)

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“…Gross et al 2003). A faint cusp of mass term variability at ∼5 days is likely the angular momentum signature of the ocean's dynamic response to barometric pressure and wind stress fluctuations associated with the gravest symmetric mode of the Rossby-Haurwitz waves (Madden 2019), see also Ponte and Ali (2002). All models suggest pronounced bottom pressure effects in χ m y around T = 20 days, a peculiarity previously noted by Bizouard and Seoane (2010).…”

Section: Oam Signal Contentsupporting

confidence: 55%

Modeling ocean-induced rapid Earth rotation variations: an update

Harker

Schindelegger

Ponte

et al. 2021

J Geod

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We revisit the problem of modeling the ocean’s contribution to rapid, non-tidal Earth rotation variations at periods of 2–120 days. Estimates of oceanic angular momentum (OAM, 2007–2011) are drawn from a suite of established circulation models and new numerical simulations, whose finest configuration is on a "Image missing"$$^\circ $$ ∘ grid. We show that the OAM product by the Earth System Modeling Group at GeoForschungsZentrum Potsdam has spurious short period variance in its equatorial motion terms, rendering the series a poor choice for describing oceanic signals in polar motion on time scales of less than $$\sim $$ ∼ 2 weeks. Accounting for OAM in rotation budgets from other models typically reduces the variance of atmosphere-corrected geodetic excitation by $$\sim $$ ∼ 54% for deconvolved polar motion and by $$\sim $$ ∼ 60% for length-of-day. Use of OAM from the "Image missing"$$^\circ $$ ∘ model does provide for an additional reduction in residual variance such that the combined oceanic–atmospheric effect explains as much as 84% of the polar motion excitation at periods < 120 days. Employing statistical analysis and bottom pressure changes from daily Gravity Recovery and Climate Experiment solutions, we highlight the tendency of ocean models run at a 1$$^\circ $$ ∘ grid spacing to misrepresent topographically constrained dynamics in some deep basins of the Southern Ocean, which has adverse effects on OAM estimates taken along the 90$$^\circ $$ ∘ meridian. Higher model resolution thus emerges as a sensible target for improving the oceanic component in broader efforts of Earth system modeling for geodetic purposes.

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Section: Oam Signal Contentsupporting

confidence: 55%

Modeling ocean-induced rapid Earth rotation variations: an update

Harker

Schindelegger

Ponte

et al. 2021

J Geod

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“…Evidence for theoretically predicted modes from linear theory in atmospheric observations and reanalyses has a long history (see e.g. Madden, 2019, and references therein).…”

Section: Normal Modes In the Three-dimensional Spherical Atmospherementioning

confidence: 99%

“…The Hough harmonics constructed with reference to the basic state at rest are thus a suitable basis for the projection. Evidence for theoretically predicted modes from linear theory in atmospheric observations and reanalyses has a long history (e.g., Madden, 2019, and references therein).…”

Section: Interpreting Observed Behaviour Across Scalesmentioning

confidence: 99%

Waves and coherent flows in the tropical atmosphere: New opportunities, old challenges

Stephan

Žagar

Shepherd

2021

Quart J Royal Meteoro Soc

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Atmospheric science relies on numerical models to simulate the complex multiscale nature of atmospheric variability, but our confidence in weather and climate predictions relies on theory and simplified models that describe scale interactions at a mechanistic level and can provide causal accounts of atmospheric behaviour. Global simulations at kilometre‐scale resolution are now feasible and offer new opportunities to the atmospheric science community for testing and expanding our understanding of climate variability and change. Taking full advantage of this new tool requires smart strategies for evaluating and analysing the output, especially as kilometre‐scale climate modelling will be limited to relatively short simulations with a rather small number of realizations. We here review some of the available tools for diagnosing and studying the dynamics of waves, coherent flows, and the interactions between them in terms of their ability to provide causal accounts of the behaviour seen in observations and in comprehensive simulation models. We describe their successes but also some of their limitations. The limitations are seen to be especially pronounced in the Tropics, where clouds, convection and atmospheric circulation are inextricably linked. The lack of a natural spatial truncation scale in the Tropics has given rise to many theoretical challenges, but it is for precisely this reason that the Tropics are where we might expect the largest gain from global kilometre‐scale models.

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“…The m =1 peaks suggest that the underlying waves are the RNMs (1, 2) and (1, 3), namely, 10-and 16-day waves (e.g., Forbes, 1995b;Sassi et al, 2012). Also, in the troposphere 16-day wave was observed before SSW 2010 (e.g., Figure 2 in Madden, 2019). Similarly, manifestations of 16-day waves coincided in different atmospheric layers were also reported prior to the onset of SSW 2003/2004 and explained as vertical wave propagation (Pancheva et al, 2008).…”

Section: Zonal Wave Number Evidence For Rnmsmentioning

confidence: 95%

Zonal Wave Number Diagnosis of Rossby Wave‐Like Oscillations Using Paired Ground‐Based Radars

Yamazaki

Hoffmann

et al. 2020

JGR Atmospheres

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Free traveling Rossby wave normal modes (RNMs) are often investigated through large-scale space-time spectral analyses, which therefore is subject to observational availability, especially in the mesosphere. Ground-based mesospheric observations were broadly used to identify RNMs mostly according to the periods of RNMs without resolving their horizontal scales. The current study diagnoses zonal wave numbers of RNM-like oscillations occurring in mesospheric winds observed by two meteor radars at about 79 • N. We explore four winters comprising the major stratospheric sudden warming events (SSWs) 2009, 2010, and 2013. Diagnosed are predominant oscillations at the periods of 10 and 16 days lasting mostly for three to five whole cycles. All dominant oscillations are associated with westward zonal wave number m = 1, excepting one 16-day oscillation associated with m = 2. We discuss the m = 1 oscillations as transient RNMs and the m = 2 oscillation as a secondary wave of nonlinear interaction between an RNM and a stationary Rossby wave. All the oscillations occur around onsets of the three SSWs, suggesting associations between RNMs and SSWs. For comparison, we also explore the wind collected by a similar network at 54 • N during 2012-2016. Explored is a manifestation of 5-day wave, namely, an oscillation at 5-7 days with m = 1), around the onset of SSW 2013, supporting the associations between RNMs and SSWs. Plain Language Summary Most detectable atmospheric Rossby waves are associated with atmospheric intrinsic properties, including the free traveling Rossby wave normal modes and forced resonant stationary Rossby waves. The former is less understood than the latter because they are relatively weak and often distorted by the background atmosphere. In the current work, we customize a compact wave identifying technique to estimate the horizontal wavelength of Rossby wave-like predominant 10-and 16-day oscillations detected by two arctic radars during stratospheric sudden warming events. Results illustrate that five of the six most oscillations are westward traveling with zonal wave number 1. We explain the oscillations as free transient Rossby wave normal modes.

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How I Learned to Love Normal-Mode Rossby–Haurwitz Waves

Cited by 10 publications

References 50 publications

Modeling ocean-induced rapid Earth rotation variations: an update

Modeling ocean-induced rapid Earth rotation variations: an update

Waves and coherent flows in the tropical atmosphere: New opportunities, old challenges

Zonal Wave Number Diagnosis of Rossby Wave‐Like Oscillations Using Paired Ground‐Based Radars

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