Simulation of the ENSO influence on the extra-tropical middle atmosphere
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KeywordsEl Niño Southern Oscillation (ENSO) Stationary planetary waves (SPWs) Sudden stratospheric warming (SSW) Middle and Upper Atmosphere Model (MUAM)
El Niño Southern Oscillation
Japanese 55-year Reanalysis
Multivariate ENSO Index
Modern-Era Retrospective Analysis for Research and Applications
Middle and Upper Atmosphere Model
Oceanic Niño Index
Southern Oscillation Index
stationary planetary wave
sudden stratospheric warming
Tropical deep convection is responsible for intensive rainfall and subsequent latent heat release in the low latitude troposphere. Spatial and temporal variations of the latent heat release excite planetary-scale waves and thermal tides, which, upon propagation and dissipation, affect the global circulation at higher altitudes. Another prominent atmospheric phenomenon in the tropical troposphere is the El Niño Southern Oscillation (ENSO) (Philander 1990). The ENSO is well recognized as a significant predictor of climate anomalies (Coelho and Goddard 2009; Larkin and Harrison 2005; Wu et al. 2003) whose global impact is seen not only in the tropics but in extra-tropics as well through teleconnections (Gershunov and Barnett 1998; Horel and Wallace 1981; Jin et al. 2016). The stratospheric processes are naturally involved in these teleconnections. In particular, considerable ENSO signatures have been discovered in the northern extra-tropical stratosphere in the observational data (Van Loon et al. 1982; Labitzke and Van Loon 1989; Camp and Tung 2007; Free and Seidel 2009; Butler and Polvani 2011; Xie et al. 2014a, b; Rao and Ren 2016a) and reproduced in simulations (Sassi et al. 2004; Garcia-Herrera et al. 2006; Manzini et al. 2006; Brönnimann et al. 2006; Rao and Ren 2016b). However, the changes in forcing of stationary planetary waves (SPWs) by the latent heat release dependent on the ENSO phase and contribution of this heating to the zonally averaged thermal budget of troposphere have not been considered explicitly in these studies. SPWs generated in the troposphere propagate upward into the stratosphere, where they dissipate or are nonlinearly saturated (Giannitsis and Lindzen 2009) and, thus, affect the stratospheric circulation by depositing their momentum and energy to the mean flow. If the phase velocity of a wave harmonics approaches the zonal mean wind, the direction of wave propagation changes due to refraction (Matsuno 1970) or reflection (Perlwitz and Harnik 2003; Harnik 2009; Nath et al. 2016). The reflected waves act against the incident harmonics, which can result in changes in the zonal mean flow in the troposphere (Lin 1982). In the latter study it was shown that weak westerly winds favor vertical propagation of SPWs. To the key parameters controlling the wave vertical propagation should be added the vertical shear of buoyancy frequency (Chen and Robinson 1992). Finally, vertical shears of the mean zonal wind can impede (Limpasuvan and Hartmann 2000) or enhance (Hu and Tung 2002) planetary wave propagation.
Global distributions of precipitation rates under La Niña and El Niño conditions differ substantially (Salby 2012). Latent heat release can influence SPWs at stratospheric heights in two ways: explicitly through their additional thermal forcing in the troposphere and implicitly via altering the mean zonal flow, whose distribution determines the propagation conditions of SPWs (Jacqmin and Lindzen 1985). The main purpose of the present investigation is to develop a new parameterization of atmospheric heating rates caused by latent heat release that takes into account the diurnal and longitudinal variations as well as its dependence on the ENSO phase. This parameterization has been implemented into the Middle and Upper Atmosphere Model (MUAM) (Pogoreltsev et al. 2007), and a set of ensemble simulations corresponding to the El Niño and La Niña conditions accounting for the differences in the lower boundary forcing of SPWs has been performed.
Heating rates and lower boundary conditions
In formula (2), A is the empirical constant, which depends on the precipitation rate. (A = 8.54 mW/kg corresponds to the rainfall rate of 1.6 mm/day.) Equations (1) and (2) have been successfully used to calculate the thermal forcing of nonmigrating tides (Forbes et al. 1997; Hagan and Forbe 2002). The heating rate has been calculated using the same constant A and MERRA precipitation data for selected El-Nino and La-Nina years, which then has been implanted in a new parameterization as the zonally averaged values, SPWs, and tidal components.
There are many different indices available that seek to describe ENSO events, e.g., NINO 3, NINO 3.4, Oceanic Niño Index (ONI), the Southern Oscillation Index (SOI), the Multivariate ENSO Index (MEI). In the present study, MEI has been used. It is based on the set of six main observables over the tropical Pacific variables. These six variables are sea-level pressure, zonal and meridional components of the surface wind, sea surface temperature, surface air temperature, and total cloudiness fraction of the sky (https://www.esrl.noaa.gov/psd/enso/mei/). Using the table of available MEI values (http://www.esrl.noaa.gov/psd/enso/mei/table.html) the following sets of Januaries of 1983, 1992, 1998, 2003, 2010 and of 1989, 1999, 2000, 2008, 2011 have been chosen, which are representative of El Niño and La Niña conditions, correspondingly. The composites for the latent heat release and lower boundary conditions for January of these years have been prepared using the MERRA and Japanese 55-year Reanalysis (JRA-55) (Kobayashi et al. 2015) data, respectively.
Multiple simulations with the MUAM have been performed to investigate the ENSO signal in the middle atmosphere. The latest version of MUAM includes new parameterizations: effects of orographic gravity waves (Gavrilov and Koval 2013; Gavrilov et al. 2015) and normal atmospheric modes (Pogoreltsev et al. 2014). The updated version of MUAM uses the climatological 3D distributions of ozone (Suvorova and Pogoreltsev 2011) and water vapor in the troposphere taking into account longitudinal variations (Ermakova et al. 2017). The scheme of numerical experiments is the same as described in Pogoreltsev et al. (2007): A fixed zenith angle of the Sun related to the 1st of January was used till 330 model days, and then, its seasonal changes have been included. Thus, 330–400 model days correspond to January–February and early March conditions. Two ensembles of 10 members for the El Niño and La Niña conditions have been obtained. The method of setting up different ensemble members was the same as described in Pogoreltsev et al. (2007).
Effects of the ENSO in the Northern Hemisphere extra-tropics
Summary and discussion
Model experiments and the MERRA data have been used to analyze the extra-tropical ENSO signals in the Northern Hemisphere boreal middle atmosphere. The results of simulations with the MUAM and reanalysis data demonstrate similar ENSO manifestations in the fields of the mean zonal wind, temperature, and SPW1 and SPW2 amplitudes. Stratospheric polar vortex becomes substantially weaker, and the polar region is warmer during El Niño events. At the altitudes of the upper stratosphere and mesosphere, the temperature effect has the opposite sign. The composites obtained with the MUAM simulations show that the mean zonal wind in the lower thermosphere at higher-middle latitudes is stronger during El Niño. This, however, cannot be deduced from the MERRA data. The activity of SPW1 is higher in the stratosphere and weaker at middle latitudes in the region of the stratospheric jet maximum during El Niño’s mid-winter. The simulated and observed SPW2 amplitude behaves in the opposite way and is larger in the stratosphere during La Niña. The obtained changes in SPW1 and SPW2 amplitudes under La Niña and El Niño events should affect the efficiency of the stratosphere–troposphere coupling, and the influence of stratospheric processes on circulation patterns in the troposphere can be manifested in different longitudinal sectors.
In recent studies, the question concerning the difference in the frequency of SSW events under El Niño and La Niña conditions has been discussed (Taguchi and Hartmann 2006; Butler and Polvani 2011; Garfinkel et al. 2012). The analysis of the MERRA data performed for years with different ENSO phases and the results of simulations with the MUAM show that the development of SSWs during the El Niño and La Niña events proceeds somewhat differently. The main heating of the polar region during La Niña is situated in the upper stratosphere (the altitude of about 40 km), and the major SSWs could not be identified in this case basing on the analysis of the temperature and mean zonal wind behavior at 10 hPa level (Pogoreltsev et al. 2015; Savenkova et al. 2017). In particular, the SSWs in January and February 2008 under the La Niña conditions cannot be identified as major warmings according to standard defining (Butler et al. 2015). The simplest way to avoid the problem is to consider the changes of the temperature and mean zonal wind at the higher altitudes and/or averaged over some altitude range, for instance, between 30 and 50 km. However, to resolve this problem the neutral ENSO phase has been considered as the next step, which helps to make a conclusion what (El Niño or La Niña) events influence extra-tropical stratosphere more significantly.
AP initiated the study and prepared the manuscript. ET wrote the initial draft version of the manuscript. MM performed the preliminary MERRA data processing. OA dealt with the parameterization of the latent heat. AP performed the ensemble simulation with the MUAM. TE and IS performed the composite analysis of the results of simulation with the MUAM and MERRA data and were involved in the discussions of results obtained. All authors contributed to interpret the results, write the discussion, and revise the manuscript. All authors read and approved the final version of the manuscript.
We appreciate the financial support (Grant Number 18-05-01050) from the Russian Foundation for Basic Research.
The authors declare that they have no competing interests.
Availability of data and materials
The results of ensemble simulation with the MUAM are available from the corresponding author upon request.
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This research was supported by the Russian Foundation for Basic Research under Grant Number 18-05-01050.
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- Ermakova TS, Statnaya IA, Fedulina IN, Suvorova EV, Pogoreltsev AI (2017) Three-dimensional semi-empirical climate model of water vapor distribution and its implementation to the radiation module of the middle and upper atmosphere model. Russ Meteorol Hydrol 42(9):594–600. https://doi.org/10.3103/S1068373917090060 CrossRefGoogle Scholar
- Hong S-S, Wang P-H (1980) On the thermal excitation of atmospheric tides. Bull Geophys 19:56–84Google Scholar
- Labitzke K, Van Loon H (1989) The Southern Oscillation. Part IX: the influence of volcanic eruptions on the Southern Oscillation in the stratosphere. J Clim 2:1223–1226. https://doi.org/10.1175/1520-0442(1989)002%3c1223:tsopit%3e2.0.co;2
- Philander SGH (1990) El Niño, La Niña and the southern oscillation. Academic Pres, San Diego, p 289Google Scholar
- Pogoreltsev AI, Savenkova EN, Aniskina OG, Ermakova TS, Chen W, Wei K (2015) Interannual and intraseasonal variability of stratospheric dynamics and stratosphere–troposphere coupling during northern winter. J Atmos Solar-Terr Phys 136, Part B:187–200. https://doi.org/10.1016/j.jastp.2015.08.008 CrossRefGoogle Scholar
- Salby ML (2012) Physics of the atmosphere and climate, 2nd edn. University Press, CambridgeGoogle Scholar
- Wu R, Hu Z-Z, Kirtman BP (2003) Evolution of ENSO-related rainfall anomalies in East Asia and the processes. J Climate 16:3741–3757Google Scholar
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