Guest essay by Antero Ollila
The error of the IPCC climate model is about 50% in the present time. There are two things that explain this error:
1) There is no positive water feedback in the climate, and 2) The radiative forcing of carbon dioxide is too strong.
I have developed an alternative theory for global warming (Ref. 1), which I call a Semi Empirical Climate Model (SECM). The SECM combines the major forces which have impacts on the global warming namely Greenhouse Gases (GHG), the Total Solar Irradiance (TSI), the Astronomical Harmonic Resonances (AHR), and the Volcanic Eruptions (VE) according to observational impacts.
Temperature Impacts of Total Solar Irradiance (TSI) Changes
GH gas warming effects cannot explain the temperature changes before 1750 like the Little Ice Age (LIA).
Total Solar Irradiance (TSI) changes caused by activity variations of the Sun seem to correlate well with the temperature changes. The TSI changes have been estimated by applying different proxy methods. Lean (Ref. 2) has used sunspot darkening and facular brightening data. Lean’s paper was selected for publication in Geophysical Research Letters “Top 40” edition and it was rewarded.
Lean has introduced a correlation formula between the decadally averaged proxy temperatures and the TSI:
dT = -200.44 + 0.1466*TSI from 1610 to 2000. In my study the selection of century-scale reference periods for TSI changes are selected carefully so that the AHR effect is zero and the forcings of GH gases are eliminated. The Sun causes the rest of the temperature change. The temperature changes of these reference periods caused by the Sun are 0 ⁰C, 0.24 ⁰C and 0.5 ⁰C, which are relatively great and different enough – also practically the same as found by Lean but the correlation is slightly nonlinear (Ref. 1):
dTs = -457777.75 + 671.93304 * TSI – 0.2465316 * TSI2
Nonlinearity is due to the cloudiness dependency on the TSI. This empirical relationship amplifies the direct TSI effect changes by a factor of 4.2. The amplification is due to the cloud forcing caused by the cloudiness change from 69.45 % in 1630s to 66 % in 2000s. A theory that the Sun activity variations modulate Galactic Cosmic Ray (GCR) flux in the atmosphere has been introduced by Svensmark (Ref. 3), which affect the nucleation process of water vapour into water droplets. The result is that the higher TSI value decreases cloudiness, and in this way, there is an amplification in the original TSI change.
Astronomical Harmonic Resonances (AHR) effects
The AHR theory is based on the harmonic oscillations of about 20 and 60 years in the Sun speed around the solar system barycentre (gravity centre of the solar system) caused by Jupiter and Saturn (Scafetta, Ref. 4). The gravitational forces of Jupiter and Saturn move the barycentre in the area, which has the radius of the Sun. The oscillations cause variations in the amount of dust entering the Earth’s atmosphere (Ermakov et al., Ref. 5). The optical measurement of the Infrared Astronomical Satellite (IRAS) revealed in 1983 that the Earth is embedded in a circumsolar toroid ring of dust, Fig. 2. This dust ring co-rotates around the Sun with Earth and it locates from 0.8 AU to 1.3 AU from the Sun. According to Scafetta’s spectral analysis, the peak-to-through amplitude of temperature changes are 0.3 – 0.35 ⁰C. I have found this amplitude to be about 0.34 ⁰C on the empirical basis during the last 80 years.
The space dust can change the cloudiness through the ionization in the same way as the Galactic Cosmic Rays (GCR) can do, Fig.3.
Because both GCR and AHR influence mechanisms work through the same cloudiness change process, their net effects cannot be calculated directly together. I have proposed a theory that during the maximum Sun activity period in the 2000s the AHR effect is also in maximum and during the lowest Sun activity period during the Little Ice Age (LIA) the AHR effect is zero (Ref. 1).
GH gas warming effects
In SCEM, the effects of CO2 have been calculated using the Equation (2)
dTs = 0.27 * 3.12 * ln(CO2/280) (2)
The details of these calculations can be found in this link: http://ift.tt/2m8TlYn
The warming impacts of other methane and nitrogen oxide are also based on spectral analysis calculations.
The summary of temperature effects
I have depicted the various temperature driving forces and the SCEM model calculated values in Fig. 4. Only two volcanic eruptions are included namely Tambora 1815, Krakatoa 1883.
The reference surface temperature is labelled as T-comp. During the time from 1610 to 1880, the T-comp is an average value of three temperature proxy data sets (Ref. 1). From 1880 to 1969 the average of Budyoko (1969) and Hansen (1981) data has been used. The temperature change from 1969 to 1979 is covered by the GISS-2017 data and thereafter by UAH.
In Fig. 5 is depicted the temperatures from 2016 onward are based on four different scenarios, in which the Sun’s insolation decreases from 0 kW to -3 kW in the following 35 years and the CO2 increases 3 ppm yearly.
The Sun’s activity has been decreasing since the latest solar cycles 23 and 24, and a new two dynamo model of the Sun of Shephard et al. (Ref. 6) predicts that its activity approaches the conditions, where the sunspots disappear almost completely during the next two solar cycles like during the Maunder minimum.
The temperature effects of different mechanisms can be summarized as follows:
The GHG effects cannot alone explain the temperature changes starting from the LIA. The known TSI variations have a major role in explaining the warming before 1880. There are two warming periods since 1930 and the cycling AHR effects can explain these periods of 60-year intervals. In 2015 the warming impact of GH gases is 37.3 %, when in the IPCC model it is 97.9 %. The SECM explains the temperature changes from 1630 to 2015 with the standard error of 0.09 ⁰C, and the coefficient of determination r2 being 0.90. The temperature increase according to SCEM from 1880 to 2015 is 0.76 ⁰C distributed between the Sun 0.35 ⁰C, the GHGs 0.28 ⁰C (CO2 0.22 ⁰C), and the AHR 0.13 ⁰C.
1. Ollila A. Semi empirical model of global warming including cosmic forces, greenhouse gases, and volcanic eruptions. Phys Sc Int J 2017; 15: 1-14.
2. Lean J. Solar Irradiance Reconstruction, IGBP PAGES/World Data Center for Paleoclimatology Data Contribution Series # 2004-035, NOAA/NGDC Paleoclimatology Program, Boulder CO, USA, 2004.
3. Svensmark H. Influence of cosmic rays on earth’s climate. Ph Rev Let 1998; 81: 5027-5030.
4. Scafetta N. Empirical evidence for a celestial origin of the climate oscillations and its implications. J Atmos Sol-Terr Phy 2010; 72: 951-970.
5. Ermakov V, Okhlopkov V, Stozhkov Y, et al. Influence of cosmic rays and cosmic dust on the atmosphere and Earth’s climate. Bull Russ Acad Sc Ph 2009; 73: 434-436.
6. Shepherd SJ, Zharkov SI and Zharkova VV. Prediction of solar activity from solar background magnetic field variations in cycles 21-23. Astrophys J 2014; 795: 46.
The paper is published in Science Domain International:
Semi Empirical Model of Global Warming Including Cosmic Forces, Greenhouse Gases, and Volcanic Eruptions
Department of Civil and Environmental Engineering (Emer.), School of Engineering, Aalto University, Espoo, Finland
In this paper, the author describes a semi empirical climate model (SECM) including the major forces which have impacts on the global warming namely Greenhouse Gases (GHG), the Total Solar Irradiance (TSI), the Astronomical Harmonic Resonances (AHR), and the Volcanic Eruptions (VE). The effects of GHGs have been calculated based on the spectral analysis methods. The GHG effects cannot alone explain the temperature changes starting from the Little Ice Age (LIA). The known TSI variations have a major role in explaining the warming before 1880. There are two warming periods since 1930 and the cycling AHR effects can explain these periods of 60 year intervals. The warming mechanisms of TSI and AHR include the cloudiness changes and these quantitative effects are based on empirical temperature changes. The AHR effects depend on the TSI, because their impact mechanisms are proposed to happen through cloudiness changes and TSI amplification mechanism happen in the same way. Two major volcanic eruptions, which can be detected in the global temperature data, are included. The author has reconstructed the global temperature data from 1630 to 2015 utilizing the published temperature estimates for the period 1600 – 1880, and for the period 1880 – 2015 he has used the two measurement based data sets of the 1970s together with two present data sets. The SECM explains the temperature changes from 1630 to 2015 with the standard error of 0.09°C, and the coefficient of determination r2 being 0.90. The temperature increase according to SCEM from 1880 to 2015 is 0.76°C distributed between the Sun 0.35°C, the GHGs 0.28°C (CO20.22°C), and the AHR 0.13°C. The AHR effects can explain the temperature pause of the 2000s. The scenarios of four different TSI trends from 2015 to 2100 show that the temperature decreases even if the TSI would remain at the present level.
Open access: http://ift.tt/2zaDjzu
via Watts Up With That?
November 21, 2017 at 09:05PM