A.V. Mikhailov(1), L. Perrone(2) Long-term variations of exospheric temperature inferred from foF1 observations A.V. Mikhailov(1), L. Perrone(2) (1) Institute of Terrestrial Magnetism, Ionosphere and Radio Wave Propagation, Moscow, Russia (2) National Institute of Geophysics and Volcanology, Rome, Italy

Are there any Tex long-term trends. If yes, what is their origin Are there any Tex long-term trends? If yes, what is their origin? Existing hypotheses

Today we have only a 20% CO2 increase CO2 Increase in the Earth’s Atmosphere should result in the Thermosphere Cooling Today we have only a 20% CO2 increase (Houghton et al., 2001)

It should be stressed that the CO2 impact on the temperature regime of the Earth’s atmosphere is just a hypothesis. We live in the atmosphere of the Sun and the state of the Earth’s upper atmosphere completely depends on solar activity

V. I. MAKAROV, A. G. TLATOV, D. K. CALLEBAUT and V. N. OBRIDKO Comparison of the geomagnetic activity aa11y and the variation of the global surface temperature of the Earth, T11y. Comparison of the Sun’s polar cap area occupied by unipolar magnetic field, Apz11y, and the variation of the global surface temperature of the Earth, T11y V. I. MAKAROV, A. G. TLATOV, D. K. CALLEBAUT and V. N. OBRIDKO Solar Physics 206: 383–399, 2002

Expected thermosphere CO2 cooling effect Under a doubled CO2 increase scenario the thermosphere should cool by  50K Rishbeth (1990), Rishbeth and Roble (1992) In the case of a linear dependence this gives 100% - 50K 20% - x; x = 10 K decrease in Tex Under the accepted rate of CO2 increase 5% per decade the cooling process has started  40 years (3.7 decades) ago and this gives the cooling rate  2.7 K per decade This is close to satellite drag estimates but by2 times larger, nevertheless

What do we have from observations The satellite drag Tex trend based on adjusting MSISE-00 model parameters to the observed mass density perturbations is - (1-2)K per decade (Emmert, 2015) There are no reasons not to rely on satellite drag trend estimates

What do we have from ISR observations -18 K/dec for Tex, noontime at Millstone Hill (Oliver et al., 2014) -60 K/dec under Tn=Ti at 350 km, daytime at Saint Santin (Donaldson et al., 2010) -10 to -15 K/dec under Tn=Ti, daytime at Tromso (Ogawa et al., 2014) -20 K/dec under Tn=Ti at 350 km, daytime at Millstone Hill (Zhang and Holt, 2013) Millstone Hill Tromso The difference between the two methods is 10-30 times ! Such ISR Tn trends look as unreal: their magnitude and height dependence ?

Questions to be answered One should accept: 1. Either ISR Tn trends are incorrect due to ISR method 2. Or the ISR method is correct but incorrect the Tn=Ti assumption 3. If ISR Ti trends are correct they have nothing to do with real Tex trends. 4. The third possibility is also possible: Incorrect both the Tn=Ti assumption and the ISR method

Checking the Tn=Ti assumption Equating the ion thermal energy input from electron-ion collision to that lost trough collisions with neutral particles, an approximate expression for Ti can be obtained ignoring thermal conduction (Banks and Kockarts, 1973): where α  6x106 and Nn is the neutral gas number density.

1. Tn  Ti assumption is valid only below 200-250 km Using Millstone Hill ISR Ne, Te, Ti daytime observations and MSISE00 model neutral concentrations (Ti - Tn) difference may be estimated 1. Tn  Ti assumption is valid only below 200-250 km 2. ISR Ti trends are not Tex trends

An independent estimate is needed to solve this contradiction Our self-consistent method has been applied (Mikhailov and Perrone, 2016). Thermospheric parameters (Tex, [O], [O2], [N2]) were retrieved from June noontime monthly median foF1 for the period of  5 solar cycles at some European ionosonde stations. Regression freg=a1+a2S+a3S2 of Tex with S (3-month F10.7) was used to remove solar cycle variations. The obtained δf=(fobs-freg)/fobs were 11-year smoothed

Retrieved and MSIS-86 monthly median Tex for June 12LT along with δ(Tret/Treg)11yw long-term variations Sign Insign Insign (δTex)11yw demonstrate both increasing and decreasing phases but the magnitude of these variations is small   2%.

Residual Tex trends analysis 1. Linear trends at middle latitudes estimated over all years are very small and statistically insignificant. 2. At Sodankyla (auroral zone) the trend is significant (at 99% level). Under average Tex=1000K the trend is -5 K per decade. 3. At middle latitudes practically all Tex variations can be removed using a regression with one solar activity index, (F10.7)3mon, i.e. solar activity practically totally controls Tex variations. What to do with ISR Tn trends?

ISR trends in Tn (supposing Tn=Ti) 1. Large positive trend at F1-layer heights 2. Height dependence in the F2-layer topside Millstone Hill Tromso

ISR plasma line observations provide Ne and Te/Ti ISR plasma line observations provide Ne and Te/Ti. From the distance Δ between two lines it is possible to find the Ti/mi ratio. If mean ion mass mi is known then Ti is known as well. Supposing Tn=Ti it is possible to find Tn long-term trends. The only problem which mi is used? (mi may manifest a long-term trend by itself) In routine ISR observations a fixed (O+/Ne) model and correspondingly a fixed mi model are used regardless changing geophysical conditions. Beynon, W.J.G. and P.J.S. Williams (1978), Incoherent scatter of radio waves from the ionosphere.

Problems related to mean ion mass, m+ All ISR observations demonstrate positive Ti trends below 200 km with a well- pronounced peak around 175 km (Zhang et al., 2016) which does not have any reasonable explanation. But it is known that ISR observations crucially depend on the accepted mean ion mass, m+ (Waldteufel, 1971; Beynon and Williams, 1978; Aponte et al., 2007). The problem arises at F1-region heights where ion composition (and consequently mean ion mass) changes from NO+ and O2+ in the E-region to O+ in the F2-region. Similar problem takes place with the transition from O+ to the lighter ions of H+ and He+ in the topside ionosphere.

Mean ion mass number, m+ at 175 km (left panel) 11-year smoothed δm+ along with linear trends (right panel) Trends in m+ are -(0.12 – 0.19)% per decade, significant at the 99% confidence level

Negative trend in m+ implies a negative trend in ion temperature Ti as ISR ion-line observations are sensitive to the Ti/m+ ratio In this case the ISR routine data development with an unchanged model of O+/Ne (and m+ correspondingly) overestimates real Ti resulting in a positive Ti trend at 175 km – that what is seen at all ISR facilities considered by Zhang et al. (2016)

Long-term variations of the O+/Ne ratio at 175 km (left panels) Long-term variations of the O+/Ne ratio at 175 km (left panels). Right panels – (O+/Ne)11yw with linear trends Trends are positive and significant (99%) at Sodankylä, > 95% at Juliusruh, and > 90% at Rome confidence levels.

Unchanged model of ion composition (O+/Ne ratio) is used at EISCAT 1. Solar cycle O+/Ne variations are large: (2-3) times at a fixed height 175 km and this ratio manifests long-term variations however this is not taken into account during the routine development of ISR measurements. 2. μ=16 (total O+) is supposed at h >300 km while the height of this level changes in solar cycle. 3. A decrease of μ (< 16) may explain the positive Ti trend above 400 km at EISCAT 4. Zero Ti trend at 400 km (Ogawa et al., 2014) where =16 corresponds to our very small Tex trends.

C O N C L U S I O N S 1. The Tex long-term variations inferred from foF1 over the (1958- 2015) are practically totally controlled by solar activity long-term variations. 2. After removing solar activity effects the residual Tex trends are very small and insignificant at middle latitudes. The Tex trend is negative and significant in the auroral zone (Sodankyla). This trend may reflect Ap11yw long-term variations 3. ISR Ti trends are not Tex trends 4. Unreal Tn=Ti ISR trends obtained in F1-region are due to using a fixed model of ion composition (O+/Ne) under varying geophysical conditions 5. Therefore routine ISR data may be not appropriate for long-term trend analyses