Long‐Term Variability and Tendencies in Migrating Diurnal Tide From WACCM6 Simulations During 1850–2014

Abstract

Long-term variability and tendencies in migrating diurnal tide (DW1) are investigated for the first time using a three-member ensemble of historical simulations by NCAR's Whole Atmosphere Community Climate Model, latest Version 6 (WACCM6) for 1850-2014 (165 years). The model reproduces the climatological features of the tide in temperature (T), zonal wind (U), and meridional wind (V). The amplitudes peak in the upper mesosphere and lower thermosphere (above~0.001 hPa) at the equator for T (~10 K) and over 20-30°N and S latitudes for U (~15 m/s) and V (~25 m/s). The contributions of solar cycle (SC), quasi biennial oscillation (QBO) at 10 and 30 hPa, El Niño-Southern Oscillation (ENSO), ozone depleting substances (ODS), carbon dioxide (CO 2), and stratospheric sulfate aerosols (volcanic eruptions) to change in annual mean amplitudes are analyzed using multiple linear regression. The tidal amplitudes in three components show a long-term increase in the upper stratosphere (0.95-10.7 hPa) and the upper mesosphere (0.0001-0.01 hPa), predominantly due to increasing CO 2 with a smaller contribution from the trend in ENSO. Interestingly, the global mean tidal amplitude in T decreases sharply after 1950-1960 until 1995 and then increases in association with changes in ODSs. The seasonal differences in tidal responses to the above indices can be as large as the overall signals. All the responses are stronger in the upper mesosphere; however, there is also a pronounced negative response of temperature tide to ODSs over middle to high latitudes around the stratopause (~1 hPa) during all seasons.

Interannual Variability of the 12‐hr Tide in the Mesosphere and Lower Thermosphere in 15 Years of Meteor‐Radar Observations Over Rothera (68°S, 68°W)

“…(2017) and Ramesh et al. (2020), we begin with the tidal anomaly. This is defined as the deviation of each month from the climatological mean.…”

“…We will now explain our linear regression analysis of the 12-hr tidal amplitudes. Similarly to Gan et al (2017) and Ramesh et al (2020), we begin with the tidal anomaly. This is defined as the deviation of each month from the climatological mean.…”

Would El Niño enhance or suppress the migrating diurnal tide in the MLT region?

“…Then, the winter (DJF) mean of the DW1 anomalies is calculated. Natural forcing, such as the solar cycle (represented by F107), QBO, ENSO, and long-term trends, jointly affect the DW1 tidal amplitude (e.g., Dhadly et al, 2018;Gurubaran et al, 2005;Gurubaran & Rajaram, 1999;Lieberman et al, 2007;Liu et al, 2017;Pedatella & Liu, 2012;Sridharan, 2019Sridharan, , 2020Sridharan et al, 2010;Vincent et al, 1998;Xu et al, 2009). To isolate the linear forcing of ENSO from the interference of other factors, a multivariate linear regression (MLR) analysis is applied on the anomalous time series at each latitude and altitude, the same as that used in Li et al (2013).…”

“…As suggested by the WACCM version 6 simulations with self-generated QBO and ENSO, there is a positive response of the MLT DW1 tide to El Niño during the winter (Ramesh et al, 2020). However, Liu et al (2017) found that DW1 amplitudes are suppressed during the winters of El Niño events based on simulations of the ground-to-topside atmosphere-ionosphere for aeronomy (GAIA) model.…”

“…Diurnal migrating tides remain a significant focus of scientific research due to a lack of comprehensive understanding of their seasonal and interannual variabilities. The tidal variation in the MLT region depends on variations in the wave sources, such as the solar heating absorption in the lower atmosphere (Chapman & Lindzen, 1970), and the tidal wave propagation, which is affected by background wind variation, such as the QBO (Forbes and Vincent, 1989;McLandress, 2002b;Ramesh et al, 2020;McLandress, 2002;Mayr and Mengel, 2005). In addition to tidal sources and propagation, tidal variability is also affected by the modulation of interactions with gravity waves (GW) (Liu and Hagan, 1998;Li et al, 2009).…”