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k-man
Gym climber
SCruz
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Topic Author's Reply - Nov 21, 2014 - 02:35pm PT
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You finally figured something out.
Actually, I've know it (that you're just trolling) for quite some time, I was just being coy.
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wilbeer
Mountain climber
Terence Wilson greeneck alleghenys,ny,
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Nov 21, 2014 - 03:40pm PT
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Google "how to calculate temperature averages".
If you could not figure out your "question"from the link I directed to you,be curious ,and learn the above.
Otherwise you have a very moot point ,that actually makes you shine.
Since you do not know how the averages are calculated,how could you ask such a question.
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wilbeer
Mountain climber
Terence Wilson greeneck alleghenys,ny,
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Nov 21, 2014 - 04:06pm PT
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You have all day ,you are retired.
Learn something.
I am taking a college course again at 56.I work 2 jobs.
What I suggested above has nothing to do with Ideology.
If that's what you believe......
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wilbeer
Mountain climber
Terence Wilson greeneck alleghenys,ny,
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Nov 21, 2014 - 04:14pm PT
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You are a beauty.
You feel better now.
There has to be a few more names you could call me......lol
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Psilocyborg
climber
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Nov 21, 2014 - 04:19pm PT
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Isn't global warming a good thing? I don't want glaciers to scour the earth.
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wilbeer
Mountain climber
Terence Wilson greeneck alleghenys,ny,
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Nov 21, 2014 - 04:20pm PT
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" How then can there be an "average" if it has NOT been steady even temps for more than ten years other then the latest Hiatus to acquire an average from. "
For Posterity.
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wilbeer
Mountain climber
Terence Wilson greeneck alleghenys,ny,
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Nov 21, 2014 - 04:27pm PT
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Who deemed that?
The advent of instruments did.That is who.
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wilbeer
Mountain climber
Terence Wilson greeneck alleghenys,ny,
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Nov 21, 2014 - 04:45pm PT
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Now he is an average denier.
Yeah,It is a hoax,those people that established the first average,determined by instruments ,were all part of it .
You know ,not averaging in all the uncertainty of the near and far past .
They where blinded by their ideology from the begining.[even though those reconstructions came much later,you know the ones you rely on ]
All of em' ....sheep.
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wilbeer
Mountain climber
Terence Wilson greeneck alleghenys,ny,
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Nov 21, 2014 - 04:52pm PT
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Who is the narcissist now?Aye,The Cheif.
Have fun w/yourself.
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wilbeer
Mountain climber
Terence Wilson greeneck alleghenys,ny,
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Nov 21, 2014 - 04:56pm PT
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Mono,It is something.....
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Psilocyborg
climber
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Nov 21, 2014 - 05:18pm PT
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political line you all stand with.
you forget about the whole line of products and services you must buy and the set of ideals you must adhere to. only then will your asslimilation be complete. It is the only way to survive, because in the future, those who refuse to assimilate will be eliminated, you know.....for the good of all of mankind. Basically, if you dont shop at whole food, wear patagonia, and drive a prius, you die.
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yosemite 5.9
climber
santa cruz
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Nov 21, 2014 - 05:58pm PT
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I scanned the table of contents of the latest UN report on climate change. I was looking for some analysis of how sun cycles are affecting the climate. I could not find any. Is there anybody that point me to the analysis?
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Psilocyborg
climber
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Nov 21, 2014 - 07:02pm PT
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im going to say 75 degrees and sunny.
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Ed Hartouni
Trad climber
Livermore, CA
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Nov 21, 2014 - 07:25pm PT
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Where is this AVERAGE the NOAA, you and others keep blabbering about....
ah, maybe just read the y-axis title of the plot?
"Anomaly (ºC) relative to 1901-2000"
if you don't understand what that means it would be totally consistent with the quality of your posts...
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Ed Hartouni
Trad climber
Livermore, CA
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Nov 21, 2014 - 08:29pm PT
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I scanned the table of contents of the latest UN report on climate change. I was looking for some analysis of how sun cycles are affecting the climate. I could not find any. Is there anybody that point me to the analysis?
here it is, from IPCC WG1 AR5 report
TS.3.5 Radiative Forcing from Natural Drivers of Climate Change
Solar and volcanic forcings are the two dominant natural contributors to global climate change during the industrial era. Satellite observations of total solar irradiance (TSI) changes since 1978 show quasi-periodic cyclical variation with a period of roughly 11 years. Longer-term forcing is typically estimated by comparison of solar minima (during which variability is least). This gives a RF change of –0.04 [–0.08 to 0.00] W m⁻² between the most recent (2008) minimum and the 1986 minimum. There is some diversity in the estimated trends of the composites of various satellite data, however. Secular trends of TSI before the start of satellite observations rely on a number of indirect proxies. The best estimate of RF from TSI changes over the industrial era is 0.05 [0.00 to 0.10] W m⁻² (medium confidence), which includes greater RF up to around 1980 and then a small downward trend. This RF estimate is substantially smaller than the AR4 estimate due to the addition of the latest solar cycle and inconsistencies in how solar RF was estimated in earlier IPCC assessments. The recent solar minimum appears to have been unusually low and long-lasting and several projections indicate lower TSI for the forthcoming decades. However, current abilities to project solar irradiance are extremely limited so that there is very low confidence concerning future solar forcing. Nonetheless, there is a high confidence that 21st century solar forcing will be much smaller than the projected increased forcing due to GHGs. [5.2.1, 8.4; FAQ 5.1]
Changes in solar activity affect the cosmic ray flux impinging upon the Earth’s atmosphere, which has been hypothesized to affect climate through changes in cloudiness. Cosmic rays enhance aerosol nucleation and thus may affect cloud condensation nuclei production in the free troposphere, but the effect is too weak to have any climatic influence during a solar cycle or over the last century (medium evidence, high agreement) . No robust association between changes in cosmic rays and cloudiness has been identified. In the event that such an association exists, it is very unlikely to be due to cosmic ray-induced nucleation of new aerosol particles. [7.3, 7.4.6]
5.2.1.1 Orbital Forcing
The term "orbital forcing" is used to denote the incoming solar radiation changes originating from variations in Earth ́s orbital parameters as well as changes in its axial tilt. Orbital forcing is well known from precise astronomical calculations for the past and future (Laskar et al., 2004). Changes in eccentricity, longitude of perihelion (related to precession), and axial tilt (obliquity) (Berger and Loutre, 1991) predominantly affect the seasonal and latitudinal distribution and magnitude of solar energy received at the top of the atmosphere (AR4, Box 6.1; Jansen et al., 2007), and the durations and intensities of local seasons. Obliquity also modulates the annual mean insolation at any given latitude, with opposite effects at high and low latitudes. Orbital forcing is considered the pacemaker of transitions between glacials and interglacials (high confidence), although there is still no consensus on exactly how the different physical processes influenced by insolation changes interact to influence ice-sheet volume (Box 5.2; Section 5.3.2). The different orbital configurations make each glacial and interglacial period unique (Yin and Berger, 2010; Tzedakis et al., 2012a). Multi-millennial trends of temperature, Arctic sea ice, and glaciers during the current interglacial period, and specifically the last 2,000 years have been related to orbital forcing (Section 5.5).
5.2.1.2 Solar Forcing
Solar irradiance models (e.g.,Wenzler et al., 2005) have been improved to better explain the instrumental measurements of total solar irradiance (TSI) and spectral (wavelength dependent) solar irradiance (SSI). Typical changes measured over an 11-year solar cycle are 0.1% for TSI and up to several percent for the ultra-violet (UV) part of SSI (see Section 8.4). Changes in TSI directly impact the Earth’s surface (see solar Box 10.2), whereas changes in UV primarily affect the stratosphere, but can influence the tropospheric circulation through dynamical coupling (Haigh, 1996). Most models attribute all TSI and SSI changes exclusively to magnetic phenomena at the solar surface (sunspots, faculae, magnetic network), neglecting any potential internal phenomena such as changes in energy transport (see also Section 8.4). The basic concept in solar models is to divide the solar surface into different magnetic features each with a specific radiative flux. The balance of contrasting dark sunspots and bright faculae and magnetic network leads to a higher TSI value during solar cycle maxima and at most wavelengths, but some wavelengths may be out of phase with the solar cycle (Harder et al., 2009; Cahalan et al., 2010; Haigh et al., 2010). TSI and SSI are calculated by adding the radiative fluxes of all features plus the contribution from the magnetically inactive surface. These models can successfully reproduce the measured TSI changes between 1978 and 2003 (Balmaceda et al., 2007; Crouch et al., 2008), but not necessarily the last minimum of 2008 (Krivova et al., 2011). This approach requires detailed information of all the magnetic features and their temporal changes (Wenzler et al., 2006; Krivova and Solanki, 2008) (see Section 8.4).
The extension of TSI and SSI into the pre-satellite period poses two main challenges. First, the satellite period (since 1978) used to calibrate the solar irradiance models does not show any significant long-term trend. Second, information about the various magnetic features at the solar surface decreases back in time and must be deduced from proxies such as sunspot counts for the last 400 years and cosmogenic radionuclides (10Be and 14C) for the past Millennium (Muscheler et al., 2007; Delaygue and Bard, 2011) and the Holocene (Table 5.1) (Steinhilber et al., 2009; Vieira et al., 2011). 10Be and 14C records not only reflect solar activity, but also the geomagnetic field intensity and effects of their respective geochemical cycles and transport pathways (Pedro et al., 2011; Steinhilber et al., 2012). The corrections for these non-solar components, which are difficult to quantify, contribute to the overall error of the reconstructions (grey band in Figure 5.1c).
TSI reconstructions are characterized by distinct grand solar minima lasting 50–100 years (e.g., the Maunder Minimum, 1645–1715) that are superimposed upon long-term changes. Spectral analysis of TSI records reveals periodicities of 87, 104, 150, 208, 350, 510, ~980, and ~2200 years (Figure 5.1d) (Stuiver and Braziunas, 1993), but with time varying amplitudes (Steinhilber et al., 2009; Vieira et al., 2011). All reconstructions rely ultimately on the same data (sunspots and cosmogenic radionuclides), but differ in the details of the methodologies. As a result the reconstructions agree rather well in their shape, but differ in their amplitude (Figure 5.1b) (Wang et al., 2005; Krivova et al., 2011; Lean et al., 2011; Schrijver et al., 2011) (see Section 8.4.1).
Since AR4, Most recent reconstructions show a considerably smaller difference (less than 0.1%) in TSI between the late 20th century and the Late Maunder Minimum (1675-1715) when the sun was very quiet, compared to the often used reconstruction of Lean et al. (1995b) (0.24%) and Shapiro et al. (2011) (~0.4%). The Lean et al. (1995a) reconstruction has been used to scale solar forcing in simulations of the last millennium prior to PMIP3/CMIP5 (Table 5.A.1). PMIP3/CMIP5 last millennium simulations have used the weak solar forcing of recent reconstructions of TSI (Schmidt et al., 2011; Schmidt et al., 2012b) calibrated (Muscheler et al., 2007; Delaygue and Bard, 2011) or spliced (Steinhilber et al., 2009; Vieira and Solanki, 2010) to Wang et al. (2005). The larger range of past TSI variability in Shapiro et al. (2011) is not supported by studies of magnetic field indicators that suggest smaller changes over the 19th and 20th centuries (Svalgaard and Cliver, 2010; Lockwood and Owens, 2011).
Note that: (1) the recent new measurement of the absolute value of TSI and TSI changes during the past decades are assessed in Section 8.4.1.1; (2) the current state of understanding the effects of galactic cosmic rays on clouds is assessed in Sections 7.4.6 and 8.4.1.5 and (3) the use of solar forcing in simulations of the last millennium is discussed in Section 5.3.5.
Figure 5.1: (a) Two reconstructions of volcanic forcing for the past 1000 years derived from ice core sulphate and used for PMIP3/CMIP5 simulations (Schmidt et al., 2011). GRA: (Gao et al., 2012); CEA: (Crowley and Unterman, 2013). Volcanic sulphate peaks identified from their isotopic composition as originating from the stratosphere are indicated by squares (green: Greenland; brown: Antarctica) (Baroni et al., 2008; Cole-Dai et al., 2009). (b) Reconstructed TSI anomalies back to the year 1000. Proxies of solar activity (e.g., sunspots, 10Be) are used to estimate the parameters of the models or directly TSI. All records except LBB (Lean et al., 1995b) have been used for PMIP3/CMIP5 simulations (Schmidt et al., 2011). DB: (Delaygue and Bard, 2011); MEA: (Muscheler et al., 2007); SBF: (Steinhilber et al., 2009); WLS: (Wang et al., 2005); VSK: (Vieira et al., 2011). Prior to 1600, the 11-year cycle has been added artificially to the original data with an amplitude proportional to the mean level of TSI. (c) Reconstructed TSI anomalies (100-year low- pass filtered; grey shading: 1 standard deviation uncertainty range) for the past 9300 years (Steinhilber et al., 2009). The reconstruction is based on 10Be and calibrated using the relationship between instrumental data of the open magnetic field, which modulates the production of 10Be, and TSI for the past 4 solar minima. The yellow band indicates the past 1000 years shown in more details in panels a and b. Anomalies are relative to the 1976–2006 mean value (1366.14 W m⁻²) of Wang et al. (2005). d) Wavelet analysis (Torrence and Compo, 1998) of TSI anomalies from panel c with dashed white lines highlighting significant periodicities (Stuiver and Braziunas, 1993).
8.4.1 Solar Irradiance
In earlier IPCC reports the forcing was estimated as the instantaneous RF at TOA. However, due to wavelength-albedo dependence, solar radiation-wavelength dependence and absorption within the stratosphere and the resulting stratospheric adjustment, the RF is reduced to ~78% of the TOA instantaneous RF (Gray et al., 2009). There is low confidence in the exact value of this number, which can be model and timescale dependent (Gregory et al., 2004; Hansen et al., 2005). AR4 gives an 11-year running mean instantaneous TOA RF between 1750 and the present of 0.12 W m⁻² with a range of estimates of 0.06–0.30 W m⁻², equivalent to a RF of 0.09 W m⁻² with a range of 0.05–0.23 W m⁻². For a consistent treatment of all forcing agents, hereafter we use RF while numbers quoted from AR4 will be provided both as RF and instantaneous RF at TOA.
8.4.1.1 Satellite Measurements of Total Solar Irradiance (TSI)
TSI measured by the Total Irradiance Monitor (TIM) on the spaceborne Solar Radiation and Climate Experiment (SORCE) is 1360.8 ± 0.5 W m⁻² during 2008 (Kopp and Lean, 2011) which is ~4.5 W m⁻² lower than the Physikalisch-Meteorologisches Observatorium Davos (PMOD) TSI composite during 2008 (Frohlich, 2009).The difference is probably due to instrumental biases in measurements prior to TIM. Measurements with the PREcision MOnitor Sensor (PREMOS) instrument support the TIM absolute values (Kopp and Lean, 2011). The TIM calibration is also better linked to national standards which provides further support that it is the most accurate (see Supplementary Material Section 8.SM.6). Given the lower TIM TSI values relative to currently used standards, most general circulation models are calibrated to incorrectly high values. However, the few tenths of a percent bias in the absolute TSI value has minimal consequences for climate simulations because the larger uncertainties in cloud properties have a greater effect on the radiative balance. As the maximum-to-minimum TSI relative change is well-constrained from observations, and historical variations are calculated as changes relative to modern values, a revision of the absolute value of TSI affects RF by the same fraction as it affects TSI. The downward revision of TIM TSI with respect to PMOD, being 0.3%, thus has a negligible impact on RF, which is given with a relative uncertainty of several tens of percent.
Since 1978, several independent space-based instruments have directly measured the TSI. Three main composite series were constructed, referred to as the Active Cavity Radiometer Irradiance Monitor (ACRIM) (Willson and Mordvinov, 2003), the Royal Meteorological Institute of Belgium (RMIB) (Dewitte et al., 2004) and the PMOD (Frohlich, 2006) series. There are two major differences between ACRIM and PMOD. The first is the rapid drift in calibration between PMOD and ACRIM before 1981. This arises because both composites employ the Hickey-Frieden (HF) radiometer data for this interval, while a re-evaluation of the early HF degradation has been implemented by PMOD but not by ACRIM. The second one, involving also RMIB, is the bridging of the gap between the end of ACRIM I (mid-1989) and the beginning of ACRIM II (late 1991) observations, as it is possible that a change in HF data occurred during this gap. This possibility is neglected in ACRIM and thus its TSI increases by more than 0.5 W m⁻² during solar cycle (SC 22). These differences lead to different long-term TSI trends in the three composites (see Figure 8.10): ACRIM rises until 1996 and subsequently declines, RMIB has an upward trend through 2008 and PMOD shows a decline since 1986 which unlike the other two composites, follows the solar-cycle-averaged sunspot number (Lockwood, 2010). Moreover, the ACRIM trend implies that the TSI on time scales longer than the SC is positively correlated with the cosmic ray variation indicating a decline in TSI throughout most of the 20th century (the opposite to most TSI reconstructions produced to date, see 8.4.1.2). Furthermore, extrapolating the ACRIM TSI long-term drift would imply a brighter Sun in the Maunder minimum (MM) than now, again opposite to most TSI reconstructions (Lockwood and Frohlich, 2008). Finally, analysis of instrument degradation and pointing issues (Lee et al., 1995) and independent modeling based on solar magnetograms (Wenzler et al., 2009; Ball et al., 2012), confirm the need for correction of HF data, and we conclude that PMOD is more accurate than the other composites.
TSI variations of ~0.1% were observed between the maximum and minimum of the 11-year SC in the three composites mentioned above (Kopp and Lean, 2011). This variation is mainly due to an interplay between relatively dark sunspots, bright faculae and bright network elements (Foukal and Lean, 1988; see Section 5.2.1.2). A declining trend since 1986 in PMOD solar minima is evidenced in Figure 8.10. Considering the PMOD solar minima values of 1986 and 2008, the RF is –0.04 W m⁻². Our assessment of the uncertainty range of changes in TSI between 1986 and 2008 is –0.08 to 0.0 W m⁻² and includes the uncertainty in the PMOD data (Frohlich, 2009; see Supplementary Material Section 8.SM.6) but is extended to also take into account the uncertainty of combining the satellite data.
For incorporation of TIM data with the previous and overlapping data, in Figure 8.10 we have standardized the composite time series to the TIM series (over 2003–2012, the procedure is explained in Supplementary Material Section 8.SM.6. Moreover as we consider annual averages, ACRIM and PMOD start at 1979 because for 1978 both composites have only two months data.
Figure 8.10: Annual average composites of measured Total Solar Irradiance: The Active Cavity Radiometer Irradiance Monitor (ACRIM) (Willson and Mordvinov, 2003), the Physikalisch-Meteorologisches Observatorium Davos (PMOD) (Frohlich, 2006) and the Royal Meteorological Institute of Belgium (RMIB) (Dewitte et al., 2004).These composites are standardized to the annual average (2003–2012) Total Solar Irradiance Monitor (TIM) (Kopp and Lean, 2011) measurements that are also shown.
8.4.1.2 TSI Variations since Preindustrial Time
The year 1750, which is used as the preindustrial reference for estimating RF, corresponds to a maximum of the 11-year SC. Trend analysis are usually performed over the minima of the solar cycles that are more stable. For such trend estimates, it is then better to use the closest SC minimum, which is in 1745. To avoid trends caused by comparing different portions of the solar cycle, we analyze TSI changes using multi-year running means. For the best estimate we use a recent TSI reconstruction by Krivova et al. (2010) between 1745 and 1973 and from 1974 to 2012 by Ball et al. (2012). The reconstruction is based on physical modeling of the evolution of solar surface magnetic flux, and its relationship with sunspot group number (before 1974) and sunspot umbra and penumbra and faculae afterwards. This provides a more detailed reconstruction than other models (see the time series in Supplementary Material Table 8.SM.3). The best estimate from our assessment of the most reliable TSI reconstruction gives a 7-year running mean RF between the minima of 1745 and 2008 of 0.05 W m⁻². Our assessment of the range of RF from TSI changes is 0.0–0.10 W m⁻² which covers several updated reconstructions using the same 7-year running mean past-to- present minima years (Wang et al., 2005; Steinhilber et al., 2009; Delaygue and Bard, 2011), see Supplementary Material Table 8.SM.4. All reconstructions rely on indirect proxies that inherently do not give consistent results. There are relatively large discrepancies among the models (see Figure 8.11).With these considerations, we adopt this value and range for AR5. This RF is almost half of that in AR4, in part because the AR4 estimate was based on the previous solar cycle minimum while the AR5 estimate includes the drop of TSI in 2008 compared to the previous two SC minima (see 8.4.1). Concerning the uncertainty range, in AR4 the upper limit corresponded to the reconstruction of Lean (2000), based on the reduced brightness of non-cycling Sun-like stars assumed typical of a Maunder minimum (MM) state. The use of such stellar analogues was based on the work of Baliunas and Jastrow (1990), but more recent surveys have not reproduced their results and suggest that the selection of the original set was flawed (Hall and Lockwood, 2004; Wright, 2004); the lower limit from 1750 to present in AR4 was due to the assumed increase in the amplitude of the 11-year cycle only. Thus the RF and uncertainty range have been obtained in a different way in AR5 compared to AR4. Maxima to maxima RF give a higher estimate than minima to minima RF, but the latter is more relevant for changes in solar activity. Given the medium agreement and medium evidence, this RF value has a medium confidence level (although confidence is higher for the last three decades). Figure 8.11 shows several TSI reconstructions modelled using sunspot group numbers (Wang et al., 2005; Krivova et al., 2010; Ball et al., 2012) and sunspot umbra and penumbra and faculae (Ball et al., 2012), or cosmogenic isotopes (Steinhilber et al., 2009; Delaygue and Bard, 2011). These reconstructions are standardized to PMOD solar cycle 23 (1996–2008) (see also Supplementary Material Section 8.SM.6).
For the MM-to-present AR4 gives a TOA instantaneous RF range of 0.1–0.28 W m⁻², equivalent to 0.08– 0.22 W m⁻² with the RF definition used here. The reconstructions in Schmidt et al. (2011) indicate a MM-to- present RF range of 0.08–0.18 W m⁻², which is within the AR4 range although narrower. As discussed above, the estimates based on irradiance changes in Sun-like stars are not included in this range because the methodology has been shown to be flawed. A more detailed explanation of this is found in Supplementary Material Section 8.SM.6. For details about TSI reconstructions on millennia time scales see Chapter 5, Section 5.2.1.1.
Figure 8.11: Reconstructions of Total Solar Irradiance since1745,annual resolution series from Wang et al. (2005) with and without an independent change in the background level of irradiance, Krivova et al. (2010) combined with Ball et al. (2012), and 5-year time resolution series from Steinhilber et al. (2009) and Delaygue and Bard (2011). The series are standardized to the PMOD measurements of solar cycle 23 (1996–2008) (PMOD is already standardized to TIM).
8.4.1.3 Attempts to Estimate Future Centennial Trends of TSI
Cosmogenic isotope and sunspot data (Rigozo et al., 2001; Solanki and Krivova, 2004; Abreu et al., 2008) reveal that currently the Sun is in a grand activity maximum that began ~1920 (20th century grand maximum). However, SC 23 showed an activity decline not previously seen in the satellite era (McComas et al., 2008; Smith and Balogh, 2008; Russell et al., 2010). Most current estimations suggest that the forthcoming solar cycles will have lower TSI than those for the past 30 years (Abreu et al., 2008; Lockwood et al., 2009; Rigozo et al., 2010; Russell et al., 2010). Also there are indications that the mean magnetic field in sunspots may be diminishing on decadal level. A linear expansion of the current trend may indicate that of the order of half the sunspot activity may disappear by about 2015 (Penn and Livingston, 2006). These studies only suggest that the Sun may have left the 20th century grand maximum and not that it is entering another grand minimum. But other works propose a grand minimum during the 21st century, estimating a RF within a range of -0.16 to 0.12 W m⁻² between this future minimum and the present day TSI (Jones et al., 2012). However, much more evidence is needed and at present there is very low confidence concerning future solar forcing estimates.
Nevertheless, even if there is such decrease in the solar activity, there is a high confidence that the TSI RF variations will be much smaller in magnitude than the projected increased forcing due to GHG (see Chapter 12, Section 12.3.1).
8.4.1.4 Variations in Spectral Irradiance
8.4.1.4.1 Impacts of UV variations on the stratosphere
Ozone is the main gas involved in stratospheric radiative heating. Ozone production rate variations are largely due to solar UV irradiance changes (HAIGH, 1994), with observations showing statistically significant variations in the upper stratosphere of 2–4% along the SC (Soukharev and Hood, 2006). UV variations may also produce transport-induced ozone changes due to indirect effects on circulation (Shindell et al., 2006b). Additionally, statistically significant evidence for an 11-year variation in stratospheric temperature and zonal winds is attributed to UV radiation (Frame and Gray, 2010). The direct UV heating of the background ozone is dominant and over twice as large as the ozone heating in the upper stratosphere and above, while indirect solar and terrestrial radiation through the SC-induced ozone change is dominant below about 5 hPa (Shibata and Kodera, 2005). The RF due to solar-induced ozone changes is a small fraction of the solar RF discussed in 8.4.1.1 (Gray et al., 2009).
8.4.1.4.2 Measurements of spectral irradiance
Solar spectral irradiance (SSI) variations in the far (120–200 nm) and middle (200–300 nm) ultraviolet (UV) are the primary driver for heating, composition, and dynamic changes of the stratosphere, and although these wavelengths compose a small portion of the incoming radiation they show large relative variations between the maximum and minimum of the SC compared to the corresponding TSI changes. As UV heating of the stratosphere over a SC has the potential to influence the troposphere indirectly, through dynamic coupling, and therefore climate (Haigh, 1996; Gray et al., 2010), the UV may have a more significant impact on climate than changes in TSI alone would suggest. Although this indicates that metrics based only on TSI are not appropriate, UV measurements present several controversial issues and modelling is not yet robust.
Multiple space-based measurements made in the past 30 years indicated that UV variations account for ~30% of the SC TSI variations, while ~70% were produced within the visible and infrared (Rottman, 2006). However, current models and data provide the range of 30–90% for the contribution of the UV variability below 400 nm to TSI changes (Ermolli et al., 2012), with a more probable value of ~60% (Morrill et al., 2011; Ermolli et al., 2012). The Spectral Irradiance Monitor (SIM) on board SORCE (Harder et al., 2009) shows, over the SC 23 declining phase, measurements that are rather inconsistent with prior understanding, indicating that additional validation and uncertainty estimates are needed (DeLand and Cebula, 2012; Lean and Deland, 2012). A wider exposition can be found in Supplementary Material Section 8.SM.6.
8.4.1.4.3 Reconstructions of preindustrial UV variations
The Krivova et al. (2010) reconstruction is based on what is known about spectral contrasts of different surface magnetic features and the relationship between TSI and magnetic fields. The authors interpolated backwards to the year 1610 based on sunspot group numbers and magnetic information. The Lean (2000) model is based on historical sunspot number and area and is scaled in the UV using measurements from the Solar Stellar Irradiance Comparison Experiment (SOLSTICE) on board the Upper Atmosphere Research Satellite (UARS). The results show smoothed 11-year UV SSI changes between 1750 and the present of ~25% at ~120 nm, ~8% at 130–175 nm, ~4% at 175–200 nm, and ~0.5% at 200–350 nm. Thus, the UV SSI appears to have generally increased over the past four centuries with larger trends at shorter wavelengths. As few reconstructions are available, and recent measurements suggest a poor understanding of UV variations and their relationship with solar activity, there is very low confidence in these values.
8.4.1.5 The Effects of Cosmic Rays on Clouds
Changing cloud amount or properties modify the Earth’s albedo and therefore affect climate. It has been hypothesized that cosmic ray flux create atmospheric ions which facilitates aerosol nucleation and new particle formation with a further impact on cloud formation (Dickinson, 1975; Kirkby, 2007). High solar activity means a stronger heliospheric magnetic field and thus a more efficient screen against cosmic rays. Under the hypothesis underlined above, the reduced cosmic ray flux would promote fewer clouds amplifying the warming effect expected from high solar activity. There is evidence from laboratory, field and modelling studies that ionization from cosmic ray flux may enhance aerosol nucleation in the free troposphere (Merikanto et al., 2009; Mirme et al., 2010; Kirkby et al., 2011). However there is high confidence (medium evidence and high agreement) that the cosmic ray-ionization mechanism is too weak to influence global concentrations of cloud condensation nuclei or their change over the last century or during a SC in a climatically-significant way (Harrison and Ambaum, 2010; Erlykin and Wolfendale, 2011; Snow-Kropla et al., 2011). A detailed exposition is found in Chapter 7, Section 7.4.6.
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k-man
Gym climber
SCruz
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Topic Author's Reply - Nov 22, 2014 - 09:18am PT
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MONO, EDH, KaveMAN, etal, what do you say to this tid bit that even EDH eluded to briefly some months ago...
Since you're asking me directly, I say STFU clown, you have shown that you have no intention of debating rationally.
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k-man
Gym climber
SCruz
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Topic Author's Reply - Nov 22, 2014 - 09:20am PT
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The zealots always think their means are justified.
Why don't you say what you really mean Sketch, instead of lobbing these abstract passive aggressive remarks in an attempt to sound like you have a purpose here.
In other words, do you have a point you're trying to make, or are you just showing that you have the ability to be an asshOle?
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Chiloe
Trad climber
Lee, NH
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Nov 22, 2014 - 09:28am PT
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In political fantasy it's all a vast conspiracy,
dishonest propagandists mix and match temperature records to promote their warmist agenda
While back in the physical-science world, NOAA's global temp index updated a few days ago adds to what others are saying: despite the no-show El Nino it's been a warm year so far.
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Chiloe
Trad climber
Lee, NH
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Nov 22, 2014 - 09:49am PT
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Heard an interesting talk yesterday from Hugh Ducklow, a Columbia University biogeoscientist doing research around Palmer Station in Antarctica. Dr. Ducklow started from the observation that something like 90% of the warming in the past 200 years has gone into the oceans, and one place that is coming back to land and atmosphere is the Antarctic Peninsula -- one of the most rapidly warming places on Earth. Mean JJA temperature at Faraday Station has increased about 7C since the 1950s.
Sea ice duration around the Peninsula has been declining too. I asked how that fit in the picture of greater overall Antarctic sea ice area this past winter, and he explained that the total Antarctic area averages together places where ice is increasing (e.g. Ross Sea) with others where it is decreasing (e.g. around the Peninsula), reflecting different geographies and processes. The declining ice has been particularly hard for Adélie Penguin colonies on the northern parts of the Peninsula, where populations have steeply declined. Apparently gentoo penguins like this better so their numbers are increasing. The warming (and Adélie troubles) may be spreading southwards.
Anyway, quite interesting to hear his on-the-ground (or ice) observations on the complexity of ecosystems in change.
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