MERRA Reanalysis Data Research Articles

A study of the dynamical characteristics of inertia–gravity waves in the Antarctic mesosphere combining the PANSY radar and a non-hydrostatic general circulation model

Abstract. This study aims to examine the dynamical characteristics of gravity waves with relatively low frequency in the Antarctic mesosphere via the first long-term simulation using a high-top high-resolution non-hydrostatic general circulation model (NICAM). Successive runs lasting 7 days are performed using initial conditions from the MERRA reanalysis data with an overlap of 2 days between consecutive runs in the period from April to August in 2016. The data for the analyses were compiled from the last 5 days of each run. The simulated wind fields were closely compared to the MERRA reanalysis data and to the observational data collected by a complete PANSY (Program of the Antarctic Syowa MST/IS radar) radar system installed at Syowa Station (39.6∘ E, 69.0∘ S). It is shown that the NICAM mesospheric wind fields are realistic, even though the amplitudes of the wind disturbances appear to be larger than those from the radar observations. The power spectrum of the meridional wind fluctuations at a height of 70 km has an isolated and broad peak at frequencies slightly lower than the inertial frequency, f, for latitudes from 30 to 75∘ S, while another isolated peak is observed at frequencies of approximately 2π∕8 h at latitudes from 78 to 90∘ S. The spectrum of the vertical fluxes of the zonal momentum also has an isolated peak at frequencies slightly lower than f at latitudes from 30 to 75∘ S at a height of 70 km. It is shown that these isolated peaks are primarily composed of gravity waves with horizontal wavelengths of more than 1000 km. The latitude–height structure of the momentum fluxes indicates that the isolated peaks at frequencies slightly lower than f originate from two branches of gravity wave propagation paths. It is thought that one branch originates from 75∘ S due to topographic gravity waves generated over the Antarctic Peninsula and its coast, while more than 80 % of the other branch originates from 45∘ S and includes contributions by non-orographic gravity waves. The existence of isolated peaks in the high-latitude region in the mesosphere is likely explained by the poleward propagation of quasi-inertia–gravity waves and by the accumulation of wave energies near the inertial frequency at each latitude.

Relationship between Asian monsoon strength and transport of surface aerosols to the Asian Tropopause Aerosol Layer (ATAL): interannual variability and decadal changes

Abstract. In this study, we have investigated the interannual variability and the decadal trend of carbon monoxide (CO), carbonaceous aerosols (CA) and mineral dust in the Asian Tropopause Aerosol Layer (ATAL) in relation to varying strengths of the South Asian summer monsoon (SASM) using MERRA-2 reanalysis data (2001–2015). Results show that during this period, the aforementioned ATAL constituents exhibit strong interannual variability and rising trends connected to the variations of the strength of SASM. During strong monsoon years, the Asian monsoon anticyclone (AMA) is more expansive and shifted northward compared to weak years. In spite of the effect of quenching of biomass burning emissions of CO and CA by increased precipitation, as well as the removal of CA and dust by increased washout from the surface to the mid-troposphere in monsoon regions, all three constituents are found to be more abundant in an elongated accumulation zone in the ATAL, on the southern flank of the expanded AMA. Enhanced transport to the ATAL by overshooting deep convection is found over preferred pathways in the Himalayan-Gangetic Plain (HGP) and the Sichuan Basin (SB). The long-term positive trends of ATAL CO and CA are robust, while the ATAL dust trend is weak due to its large interannual variability. The ATAL trends are associated with increasing strength of the AMA, with earlier and enhanced vertical transport of ATAL constituents by enhanced overshooting convection over the HGP and SB regions, outweighing the strong reduction of CA and dust from the surface to the mid-troposphere.

A thermodynamic climatology of the disturbed stratospheric polar vortex

A climatology of polar vortex disturbances in the Northern Hemisphere winter stratosphere is constructed from MERRA2 Reanalysis data for the winter seasons of 1981–2017. Sixty disturbances (splits or displacements) of the polar vortex are identified during the 37 winter seasons using geometric moments of stratospheric potential vorticity. The likelihood of a disturbed day is negatively correlated with the stratospheric quasi‐biennial oscillation (positively correlated with its easterly phase). It is also, surprisingly, negatively correlated with the presence of a stratospheric Aleutian anticyclone (the Aleutian high). The position of the polar vortex during each disturbance event is averaged to generate an area‐averaging filter that is applied to thermodynamic diagnostic quantities in the air column enclosed by the polar vortex. This diagnosis reveals that the location of the disturbed polar vortex experiences, on average, cooling driven by horizontal temperature advection in the lower and middle stratosphere prior to the onset of the disturbance, along with significant residual (likely adiabatic) cooling in the troposphere in the weeks surrounding the onset. How these thermodynamic signatures associated with a disturbed polar vortex relate to the Aleutian high and the quasi‐biennial oscillation is also explored.

Aerosol Optical Characteristics Retrieved from CIMEL Sun Photometer Measurements (AERONET) near St. Petersburg

The measurements with a CIMEL CE 318 sun photometer near St. Petersburg within the AERONET international monitoring network are analyzed. Typical regional aerosol optical parameters (aerosol optical depth, Angstrom exponent, and single scattering albedo) and their variations are determined. Certain regularities in variations in the aerosol parameters over the northwest region of the Russian Federation are revealed. The study is supplemented by the joint analysis of data from the nearby AERONET observation sites in Finland and Estonia, satellite measurements, and MERRA reanalysis data.

Interannual Variability of Late-spring Circulation and Diabatic Heating over the Tibetan Plateau Associated with Indian Ocean Forcing

The thermal forcing of the Tibetan Plateau (TP) during boreal spring, which involves surface sensible heating, latent heating released by convection and radiation flux heat, is critical for the seasonal and subseasonal variation of the East Asian summer monsoon. Distinct from the situation in March and April when the TP thermal forcing is modulated by the sea surface temperature anomaly (SSTA) in the North Atlantic, the present study shows that it is altered mainly by the SSTA in the Indian Ocean Basin Mode (IOBM) in May, according to in-situ observations over the TP and MERRA reanalysis data. In the positive phase of the IOBM, a local Hadley circulation is enhanced, with its ascending branch over the southwestern Indian Ocean and a descending one over the southeastern TP, leading to suppressed precipitation and weaker latent heat over the eastern TP. Meanwhile, stronger westerly flow and surface sensible heating emerges over much of the TP, along with slight variations in local net radiation flux due to cancellation between its components. The opposite trends occur in the negative phase of the IOBM. Moreover, the main associated physical processes can be validated by a series of sensitivity experiments based on an atmospheric general circulation model, FAMIL. Therefore, rather than influenced by the remote SSTAs of the northern Atlantic in the early spring, the thermal forcing of the TP is altered by the Indian Ocean SSTA in the late spring on an interannual timescale.

Seasonal Transition in PM10 Exposure and Associated All-Cause Mortality Risks in India.

Lack of a consistent PM10 (particulate matter smaller than 10 μm) database at high spatial resolution hinders in assessing the environmental impact of PM10 in India. Here we propose an alternate approach to estimate the PM10 database. Aerosol extinction coefficients at the surface are calculated from midvisible aerosol optical depth from MERRA-2 reanalysis data using characteristics vertical profiles from CALIOP and then are converted to PM10 mass using aerosol property information and microphysical data. The retrieved PM10 are bias-corrected and evaluated ( R2 = 0.85) against coincident ground-based data maintained under the Central Pollution Control Board network. PM10 exposure exceeds Indian annual air quality standard in 72.3% districts. Transition in PM10 exposure from the monsoon (Jun-Sep) to postmonsoon season (Oct-Nov) translates to 1-2% higher all-cause mortality risk over the polluted Indo-Gangetic Basin (IGB). Mortality risk increases in the central to eastern IGB and central India and reduces in Delhi national capital region in the winter (Dec-Feb) relative to the postmonsoon season. Mortality risk decreases by 0.5-1.8% in most parts of India in the premonsoon season (Mar-May). Our results quantify the vulnerability in terms of seasonal transition in all-cause mortality risks due to PM10 exposure at district level for the first time in India.

Determining variabilities of non-Gaussian wind-speed distributions using different metrics and timescales

Quantification of long-term wind-speed variability is a critical component in wind resource assessment, and effective wind-farm operations require proper assessment of this variability. Yet, wind-speed variations differ across averaging temporal scales because hourly mean wind speeds fluctuate more than yearly averages. In this study, we quantify the influence of averaging timescale to the resultant variability. We assess three spread metrics (standard deviation, coefficient of variation, and robust coefficient of variation) and two distribution measures (skewness and kurtosis) based on 38 years of wind speeds from the National Aeronautics and Space Administration’s MERRA-2 reanalysis data set over the contiguous United States. The spatial distributions of wind-speed variability differ with metrics and timescales: wind speeds of fine temporal resolution generate strong variabilities that dilute spatial contrasts; small sample size becomes a constraint in calculating interannual variabilities via annual means and leads to inaccurate results. Overall, we find that metrics based on monthly data portray the largest spatial differences of wind-speed variability. Although standard deviation yields consistent geographical projections, none of the wind-speed data of any time frame are perfectly Gaussian. Therefore, the robust coefficient of variation, a statistically robust and resistant approach, appears to be the ideal metric for quantifying wind-speed variabilities based on monthly mean data.

Spatially-explicit monitoring of crop photosynthetic capacity through the use of space-based chlorophyll fluorescence data

Plant functional traits such as photosynthetic capacity are critical parameters for terrestrial biosphere models. However, their spatial and temporal characteristics are still poorly represented. In this study, we used satellite observations of sun-induced fluorescence (SIF) to estimate top-of-canopy photosynthetic capacity (maximum carboxylation rate, Vcmax at a reference temperature of 25 °C) for crops, which was in turn utilized to simulate regional gross primary production (GPP). We first estimate the key parameter, Vcmax, in the widely-used FvCB photosynthesis model using field measurements of CO2 and water fluxes during 2007–2012 at seven crop eddy covariance flux sites over the US Corn Belt. The results showed that satellite far-red SIF retrievals have a stronger link to Vcmax at the seasonal scale (R2 = 0.70 for C4 and R2 = 0.63 for C3 crop) as compared with widely-used vegetation indices. We calibrate an empirical model linking Vcmax with SIF that was used to estimate spatially and temporally varying crop Vcmax for the US Corn Belt region. The resulting Vcmax maps are used together with meteorological data from MERRA reanalysis data and vegetation structural parameters derived from the satellite-based spectral reflectance data to constrain the Soil-Canopy Observation of Photosynthesis and Energy (SCOPE) balance model in order to estimate regional crop GPP. Our results show a substantial improvement in the seasonal and spatial patterns of cropland GPP when compared with crop yield inventory data. The evaluation with tall tower atmospheric CO2 measurements further supports our estimation of spatiotemporal Vcmax from space-borne SIF. Considering that SIF has a direct link to photosynthetic activity, our findings highlight the potential to infer regional Vcmax using remotely sensed SIF data and to use this information for a better quantification of regional cropland carbon cycles.

Quantitative synergy assessment of regional wind-solar energy resources based on MERRA reanalysis data

Considering the volatility and synergies of renewable energy sources, sufficient resource assessment is of great significance for investors and planners to reduce power fluctuations, increase integration capacity, and improve economic and social benefits. This paper proposes a tri-level framework to evaluate and visualize the spatiotemporal characteristics of regional wind and solar energy resources from the perspective of data mining. Furthermore, a free, open-source software package named Quantitative Synergy Assessment Toolbox for renewable energy sources (QSAT V1.0) has been developed with Python and hosted on GitHub, which is a useful tool for the resources assessment and preliminary regional synergetic planning. In the first level, the long-term reanalysis meteorological data of wind speed, solar irradiation and ambient temperature are acquired from MERRA, processed via virtual generation systems, and corrected by in-situ measured data. For the progressive two levels of single-site and wide-area data assessments, the data mining methods incorporating attribute construction, principal components analysis and k-means clustering are used to reduce the dimensionality and capture the temporal and spatial synergy patterns. According to the extracted patterns, the rational combinations of sub-regions can be selected as candidates to make full use of the synergies. Shandong province in China is taken as a demonstration to quantify and analyze the complementarities of solar and wind resources. The proposed method and tools can help enhance the planning of renewable energy sources.

Surface Moistening Trends in the Northern North American Great Plains Increase the Likelihood of Convective Initiation

Abstract Land management impacts atmospheric boundary layer processes, and recent trends reducing the practice of summer fallow have led to increases in precipitation and decreases in temperature in the Canadian Prairie provinces during summer. It is unclear if such trends also impact the hydrometeorology of the adjacent U.S. northern Great Plains, parts of which have seen similar changes in land management. Here, MERRA-2 reanalysis data, eddy covariance observations, and a mixed-layer (ML) atmospheric modeling framework are combined to demonstrate that the likelihood of convectively preconditioned conditions has increased by approximately 10% since the mid-1980s and is now more sensitive to further decreases in the Bowen ratio (Bo) and maximum daily net radiation in northeastern Montana. Convective season Bo in the study area has decreased from approximately 2 to 1 from the 1980s until the present, largely due to simultaneous increases in latent heat flux and decreases in sensible heat flux, consistent with observed decreases of summer fallow and increases in cropping. Daily net radiation has not changed despite a significant decrease in May and June humidity lapse rates from the 1980s to present. Future research should determine the area of the U.S. Great Plains that has seen changes in the dynamics of the atmospheric boundary layer height and lifted condensation level and their crossings as a necessary condition for convective precipitation to occur and ascertain if ongoing changes in land management will lead to future changes in convective outcomes.

An intercomparison of AOD-converted PM2.5 concentrations using different approaches for estimating aerosol vertical distribution

Due to the limited spatial coverage of surface PM2.5 monitoring sites, satellite AOD (aerosol optical depth) products have been widely used to estimate surface PM2.5 in different parts of the world. A major difficulty as well as source of uncertainty in converting AOD to PM2.5 is the determination of aerosol vertical distribution, usually represented by the boundary layer height (BLH). In this study, we evaluate the performance of different approaches of estimating aerosol vertical distributions in the AOD-PM2.5 conversion process, using long-term and multi-source data acquired at a super station, Yuen Long, Hong Kong. The monthly climatology of aerosol vertical distribution and BLH products derived from lidar, radiosonde, and MERRA reanalysis data are respectively applied for converting AOD to surface aerosol extinction coefficients. Seasonal empirical hygroscopic growth functions are constructed to convert aerosol extinction to dry PM2.5 mass concentration. Results indicate that different vertical distribution estimation approaches can have highly varying effect on the converted PM2.5 concentration. Using lidar-derived BLHs shows the best agreement, with a correlation coefficient of 0.73 and a relative bias of 30.6% between retrievals and observations. Since continuous lidar measurements are not available for most regions, the climatology pattern of aerosol structure and radiosonde-derived BLHs are found to be suitable alternatives with a correlation coefficient of ∼0.6, and considerably outperform the results using BLHs derived from reanalysis data. Elevated aerosol layers appear to be the major source of uncertainty and result in an overestimate of satellite results, especially during the spring and summer seasons.

Climate teleconnections influence on West Africa's terrestrial water storage

AbstractThere is some evidence of rapid changes in the global atmosphere and hydrological cycle caused by the influence of climate variability. In West Africa, such changes impact directly on water resources leading to incessant extreme hydro‐meteorological conditions. This study examines the association of three global climate teleconnections—El‐Niño Southern Oscillation (ENSO), Indian Ocean Dipole (IOD), and Atlantic Multi‐decadal Oscillation (AMO) with changes in terrestrial water storage (TWS) derived from both Modern‐Era Retrospective Analysis for Research and Applications (MERRA, 1980–2015) and Gravity Recovery and Climate Experiment (GRACE, 2002–2014). In the Sahel region, positive phase of AMO coincided with above‐normal rainfall (wet conditions) and the negative phase with drought conditions and confirms the observed statistically significant association (r = 0.62) between AMO and the temporal evolutions of standardised precipitation index. This relationship corroborates the observed presence of AMO‐driven TWS in much of the Sahel region (though considerably weak in some areas). Although ENSO appears to be more associated with GRACE‐derived TWS over the Volta basin (r=−0.40), this study also shows a strong presence of AMO‐ and ENSO‐induced TWS derived from MERRA reanalysis data in the coastal West African countries and most of the regions below latitude 10°N. The observed presence of ENSO‐ and AMO‐driven TWS is noticeable in tropical areas with relatively high annual/bimodal rainfall and strong inter‐annual variations in surface water. The AMO has a wider footprint and sphere of influence on the region's TWS and suggests the important role of North Atlantic Ocean. IOD‐related TWS also exists in West Africa and its influence on the region's hydrology maybe secondary and somewhat complementary. Nonetheless, presumptive evidence from the study indicates that ENSO and AMO are the two major climatic indices more likely to impact on West Africa's TWS.

Characteristics and development of European cyclones with tropical origin in reanalysis data

Major storm systems over Europe frequently have a tropical origin. This paper analyses the characteristics and dynamics of such cyclones in the observational record, using MERRA reanalysis data for the period 1979-2013. By stratifying the cyclones along three key phases of their development (tropical phase, extratropical transition and final re-intensification), we identify four radically different life cycles: the tropical cyclone and extratropical cyclone life cycles, the classic extratropical transition and the warm seclusion life cycle. More than 50% of the storms reaching Europe from low latitudes follow the warm seclusion life cycle. It also contains the strongest cyclones. They are characterized by a warm core and a frontal T-bone structure, with a northwestward warm conveyor belt and the effects of dry intrusion. Rapid deepening occurs in the latest phase, around their arrival in Europe. Both baroclinic instability and release of latent heat contribute to the strong intensification. The pressure minimum occurs often a day after entering Europe, which enhances the potential threat of warm seclusion storms for Europe. The impact of a future warmer climate on the development of these storms is discussed.

Preliminary assessment of the variability of UK offshore wind speed as a function of distance to the coast

In the UK, there is an interest in the expected offshore wind resource given ambitious national plans to expand offshore capacity. There is also an increasing interest in alternative datasets to evaluate wind seasonal and inter-annual cycles which can be very useful in the initial stages of the design of wind farms in order to identify prospective areas where local measurements can then be applied to determine small-scale variations in the marine wind climate. In this paper we analyse both MERRA2 reanalysis data and measured offshore mast data to determine patterns in wind speed variation and how they change as a function of the distance from the coast. We also identify an empirical expression to estimate wind speed based on the distance from the coast. From the analysis, it was found that the variations of the seasonal cycles seem to be almost independent of the distance to the nearest shore and that they are an order of magnitude larger than the variations of the diurnal cycles. It was concluded that the diurnal variations decreased to less than a half for places located more than 100km from the nearest shore and that the data from the MERRA2 reanalysis grid points give an under-prediction of the average values of wind speed for both the diurnal and seasonal cycles. Finally, even though the two offshore masts were almost the same nearest distance from the coast and were geographically relatively close, they exhibited significantly different behaviour in terms of the strength of their diurnal and seasonal cycles which may be due to the distance from the coast for the prevailing wind direction being quite different for the two sites.

해상풍력자원 평가를 위한 ERA-Interim/MERRA 재해석 데이터 신뢰성 평가

An investigation on reliability of reanalysis wind data was conducted using the met mast wind data at four coastal regions, Jeju Island. Shinchang, Handong, Udo and Gangjeong sites were chosen for the met mast sites, and ERA-Interim and MERRA reanalysis data at two points on the sea around Jeju Island were analyzed for creating Wind Statistics of WindPRO software. Reliability of reanalysis wind data was assessed by comparing the statistics from the met mast wind data with those from Wind Statistics of WindPRO software. The relative error was calculated for annual average wind speed, wind power density and annual energy production. In addition, Weibull wind speed distribution and monthly energy production were analyzed in detail. As a result, ERA-Interim reanalysis data was more suitable for wind resource assessment than MERRA reanalysis data.

Correlation between wind power generation in the European countries

The correlations between wind power generation in different countries are important for quantifying the reductions in variability when electrically interconnecting the countries. Hourly, country-wise time series of wind power output were generated for all European countries using MERRA reanalysis data. By comparing the model output with actual measurements, it is shown that this approach is appropriate for studying correlations. In order to deepen the analysis, correlation coefficients were not only computed for these time series, but also for the one hour step changes and for band-pass filtered data. The general pattern is that correlations reduce with separation distance in an exponential fashion and are highest for the long-term components (T > 4 months) and lowest for step changes and short-term components (T < 2 days). Interesting deviations from this pattern however exist. When comparing to earlier results for individual farms, the exponential decay is slower, in particular for step changes.

Seasonal Sensitivity of the Eddy-Driven Jet to Tropospheric Heating in an Idealized AGCM

Abstract A dry dynamical core is used to investigate the seasonal sensitivity of the circulation to two idealized thermal forcings: a tropical upper-tropospheric heating and a polar lower-tropospheric heating. The thermal forcings are held constant, and the response of the circulation in each month of the year is explored. First, the circulation responses to tropical warming and polar warming are studied separately, and then the response to the simultaneously applied forcings is analyzed. Finally, the seasonality of the internal variability of the circulation is explored as a possible mechanism to explain the seasonality of the responses. The primary results of these experiments are as follows: 1) There is a seasonal sensitivity in the circulation response to both the tropical and polar forcings. 2) The jet position response to each forcing is greatest in the transition seasons, and the jet speed response exhibits a seasonal sensitivity to both forcings, although the seasonal sensitivities are not the same. 3) The circulation response is nonlinear in the transition seasons, but approximately linear in the winter months. 4) The internal variability of the unforced circulation exhibits a seasonal sensitivity that may partly explain the seasonal sensitivity of the forced response. The seasonality of the internal variability of daily MERRA reanalysis data is compared to that of the model, demonstrating that the broad conclusions drawn from this idealized modeling study may be useful for understanding the jet response to anthropogenic forcing.

Restoring the missing high-frequency fluctuations in a wind power model based on reanalysis data

A previously developed model based on MERRA reanalysis data underestimates the high-frequency variability and step changes of hourly, aggregated wind power generation. The goal of this work is to restore these fluctuations. Since the volatility of the high-frequency signal varies in time, machine learning techniques were employed to predict the volatility. As predictors, derivatives of the output from the original “MERRA model” as well as empirical orthogonal functions of several meteorological variables were used. A FFT-IFFT approach, including a search algorithm for finding appropriate phase angles, was taken to generate a signal that was subsequently transformed to simulated high-frequency fluctuations using the predicted volatility. When comparing to the original MERRA model, the improved model output has a power spectral density and step change distribution in much better agreement with measurements. Moreover, the non-stationarity of the high-frequency fluctuations was captured to a large degree. The filtering and noise addition however resulted in a small increase in the RMS error.

Quasi‐biennial oscillation modulation of the middle‐ and high‐latitude mesospheric semidiurnal tides during August–September

AbstractThe seasonal and interannual variabilities of mesospheric semidiurnal tides (SDT) are investigated using specular meteor radar‐based winds. The horizontal wind observations during 2003 to 2014 from a high‐latitude station, Andenes (69°N, 16°E), and during 2008 to 2014 from a midlatitude station, Juliusruh (54°N, 13°E), are used. It has been observed that the amplitudes of mesospheric SDTs are enhanced at both stations during August–September of all the years. These enhancements show a systematic behavior with that of the low‐latitude stratospheric quasi‐biennial oscillation (QBO), which is characterized based on winds from radiosonde data. The SDT amplitude values during enhancement are below/above mean level for those years in which the QBO wind at 50 hPa is westward/eastward (QBOw/QBOe). The average SDT amplitudes during the August–September enhancement duration are found to vary hand in hand with the low‐latitude QBO wind, suggesting QBO modulation of SDT. Stratospheric and lower mesospheric zonal wind perturbations from MERRA reanalysis data show weak local forcing in the Northern Hemisphere and indication of enhanced quasi‐stationary planetary waves (SPW) in the Southern Hemisphere. Based on these observations and some earlier results, we hypothesize that the QBOw/QBOe wind damp/enhance the southern hemispheric SPW of wave number 1 (SPW1). This modulated SPW1 then interacts with the northern midlatitude and high‐latitude SDTs to imprint the signature of QBO on them.

Hidden staircase signal in recent climate dynamic

In this study we used HadCRUT4 monthly mean near surface temperature anomalies for 1950–2014 years in order to investigate properties of recent warming. Our aim was to separate changes produced by short-term natural variations and to look on temporal and spatial dynamics of residual temperature anomalies. For this we subtract linear influence of El Nino Southern Oscillation from each grid box of surface temperature measurements. We found that residual global temperature dynamics looks like staircase function: linear trends for three quasi-stable periods 1950–1987, 1988–1997 and 1998–2014 are near zero and near all warming occurred during two shifts of 1987/1988 and 1997/1998 years. Examples of similar staircase behavior of some climate parameters were found in NCEP/NCAR and NASA MERRA reanalysis data. Staircase signal suggests the existence of some regulation mechanism in climate system. This mechanism should maintain global temperature adjusted for El Nino Southern Oscillation near stable in 1950–1987, 1988–1997 and 1998–2014 periods nevertheless all the time growing forcing due to anthropogenic greenhouse gases.