Reply to Comment on &amp;quot;Global structure, seasonal and interannual variability of the migrating semidiurnal tide seen in the SABER/TIMED temperatures (2002–2007)&amp;quot; by Manson et al. (2010)

Pancheva, D.; Mukhtarov, Plamen; Andonov, B.

doi:10.5194/angeo-28-677-2010

Cited by 8 publications

(3 citation statements)

References 24 publications

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“…Other modes, like the antisymmetric (1, 2), (2, 3), (2, 5), (3, 4), and (3, 6) modes, also make considerable contributions to the corresponding components. These results are in agreement with the previous works [ Chang and Avery , ; Guharay and Franke , ; Mukhtarov et al ., ; Oberheide et al ., ; Pancheva et al ., ; Xue et al ., ; Yuan et al ., ].…”

Section: Data Analysis and Resultsmentioning

confidence: 99%

Tidal wind mapping from observations of a meteor radar chain in December 2011

Wan

Ning

et al. 2013

JGR Space Physics

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[1] This article proposes a technique to map the tidal winds in the mesosphere and lower thermosphere (MLT) region from the observations of a four-station meteor radar chain located at middle-and low-latitudes along the 120 E meridian in the Northern Hemisphere. A 1 month dataset of the horizontal winds in the altitude range of 80-100 km is observed during December 2011. We first decompose the tidal winds into mean, diurnal, semidiurnal, and terdiurnal components for each station. It is found that the diurnal/semidiurnal components dominate at the low-latitude/midlatitude stations. Their amplitudes increase at lower altitudes and then decrease at higher altitudes after reaching a peak in the MLT region. Hough functions of the classical tidal theory are then used to fit the latitudinal distribution of each decomposed component. The diurnal component is found to be dominated by the first symmetric (1, 1) mode. Yet for the semidiurnal and terdiurnal components, the corresponding dominant modes are the second symmetric modes (2, 4) and (3, 5), and considerable contributions are also from the first antisymmetric modes (2, 3), (3, 4) and second antisymmetric modes (2, 5), (3, 6). Based on the decomposed results, we further map the horizontal winds in the domains of latitude, altitude and local time. The mapped horizontal winds successfully reproduce the local time versus altitudinal distributions of the original observations at the four stations. Thus, we conclude that the meteor radar chain is useful to monitor and study the regional characteristics of the tidal winds in the MLT region.

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Section: Data Analysis and Resultsmentioning

confidence: 99%

Tidal wind mapping from observations of a meteor radar chain in December 2011

Wan

Ning

et al. 2013

JGR Space Physics

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“…SABER diagnostics using 60‐day running mean Fourier fits indicates ≥10‐K amplitude of the semidiurnal tide at altitudes ≥100 km in the 20–40° latitude range between April and September in the Southern Hemisphere and October to March in the Northern Hemisphere, respectively, but comparatively small (≤5 K) amplitudes equatorward of 20° (e.g., Akmaev et al, ). Note that semidiurnal tidal amplitudes decrease rapidly toward lower altitudes at all latitudes, that is, ≤5 K in the 20–40° latitude range at 90 km (Pancheva et al, ). Equation suggests that the semidiurnal aliasing can be estimated as the semidiurnal amplitude times

sin ((), \frac{π}{6} ∆ t)

.…”

Section: Model and Sabermentioning

confidence: 98%

Statistical Modeling of Tidal Weather in the Mesosphere and Lower Thermosphere

Vitharana

Zhu

et al. 2019

JGR Atmospheres

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We study the statistical properties of tidal weather (variability period <30 days) of DW1 amplitude using the extended Canadian Middle Atmospheric Model (eCMAM) and Sounding of the Atmosphere using Broadband Emission Radiometry (SABER). A hierarchy of statistical models, for example, the autoregressive (AR), vector AR, and parsimonious vector AR models, are built to predict tidal weather. The quasi 23‐day oscillation found in the tidal weather is a key parameter in the statistical models. Comparing to the more complex vector AR and parsimonious vector AR models, which consider the spatial correlations of tidal weather, the simplest AR model can predict one‐day tidal weather with an accuracy of 89% (R2: correlation coefficient squared). In the AR model, 23 coefficients at each latitude and height are obtained from seven years of eCMAM data. Tidal weather is predicted via a linear combination of 23 days of tidal weather data prior to the prediction day. Different sensitivity tests are performed to prove the robustness of these coefficients. These coefficients obtained from eCMAM are in very good agreement with those from SABER. SABER tidal weather is predicted with an accuracy of 86% and 87% at one day by the AR models with coefficients from eCMAM and SABER, respectively. The five‐day forecast accuracy is between 60 and 65%.

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“…These waves profoundly affect the large‐scale dynamics of the mesosphere and lower thermosphere (MLT) where they attain large amplitudes and dominate the large‐scale atmospheric fields. Recent studies based on the observations made by the Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) and the TIMED Doppler Interferometer (TIDI) instruments on the Thermosphere‐Ionosphere‐Mesosphere‐Energetics and Dynamics (TIMED) satellite have provided new insight into tidal fields and revealed the global distribution and climatology of the most important tidal components in temperature and neutral winds respectively [e.g., Zhang et al , 2006; Huang et al , 2006a, 2006b; Forbes et al , 2006; Oberheide et al , 2007; Oberheide and Forbes , 2008; Mukhtarov et al , 2009; Xu et al , 2009; Pancheva et al , 2009a, 2010a; Pancheva and Mukhtarov , 2011a]. Some of the above mentioned studies clearly suggested that the nonmigrating tides are much larger than previous anticipated and often exceed the migrating tide counterparts in the lower thermosphere [e.g., Zhang et al , 2006; Forbes et al , 2006, 2008; Oberheide et al , 2006, 2007; Pancheva et al , 2009b, 2010b].…”

Section: Introductionmentioning

confidence: 99%

Global response of the ionosphere to atmospheric tides forced from below: Comparison between COSMIC measurements and simulations by atmosphere‐ionosphere coupled model GAIA

et al. 2012

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This paper for the first time presents a detailed comparison between simulated and observed global electron density responses to different atmospheric tides forced from below. The recently developed Earth's whole atmospheric model from the troposphere to the ionosphere, called GAIA, has been used for the simulation of the electron density tidal responses. They have been compared with the extracted from the COSMIC electron density data tidal responses for the period of time October 2007 to March 2009. Particular attention has been paid to the nonmigrating DE3/DE2 and migrating DW1, SW2 and TW3 electron density responses. The GAIA model reproduced quite well the COSMIC DE3/DE2 responses. Both simulations and observations revealed three altitude regions of enhanced electron density responses: (1) an upper level response, above 300 km height, apparently shaped mainly by the “fountain effect”; (2) a response located near altitudes of ∼200–270 km, and (3) a lower thermospheric response situated near 120–150 km height. A possible mechanism is suggested for explaining the two lower level responses. For the first time the GAIA model simulations supported the observational evidence found in the COSMIC measurements that the ionospheric WN4 (WN3) longitude structure is not generated only by the DE3 (DE2) tide as it has been often assumed. As regards the comparison of the migrating DW1, SW2 and TW3 responses the obtained results clearly demonstrate that the GAIA model reproduce very well of the SW2 and TW3 COSMIC electron density responses. The only main discrepancy is seen in the migrating DW1 response; the observation does not support the splitting of the simulated response at both sides of the equator. This is due mainly to the difference between the SABER and GAIA SW2 tide in the lower thermosphere as it turned out that the DW1 electron density response strongly depends on the mean features of the lower thermospheric SW2 tide.

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Reply to Comment on "Global structure, seasonal and interannual variability of the migrating semidiurnal tide seen in the SABER/TIMED temperatures (2002–2007)" by Manson et al. (2010)

Cited by 8 publications

References 24 publications

Tidal wind mapping from observations of a meteor radar chain in December 2011

Tidal wind mapping from observations of a meteor radar chain in December 2011

Statistical Modeling of Tidal Weather in the Mesosphere and Lower Thermosphere

Global response of the ionosphere to atmospheric tides forced from below: Comparison between COSMIC measurements and simulations by atmosphere‐ionosphere coupled model GAIA

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