Solar activity depicts a great deal of variability even during the last 400 years of telescopic sunspot observations since 1610 AD (see Figure 2, Chapter2.5). One can clearly see that there was almost no sunspots during more than a half of a century in 1645–1700 AD. It is important to understand that this lack ofsunspots at this time is not due to the lack of sunspot observations. In fact, the Sun was observed by several astronomers already at this time. However, there was little to observe since the solar surface was almost spotless. Some of these early observers wrote weary comments in their notebooks: another year with nosunspots. This pe-riod is now known as theMaunder minimum, named after the British astronomer Edward Walter Maunder (1851–1928) (Eddy, 1976). Such a quiet state of the Sun (or another star), when the regular cyclic appearance ofsunspots is greatly suppressed for several decades (from 40 to 200 years), is more generally called the Grand minimumof activity. Grand minima should not be confused with the nor-mal sunspot minima of the 11-yearsolar cyclethat only last for a couple of years.
Another interesting feature of the Sun in recent times is the very high level of sunspot activity during most of the last century, roughly from the 1930s to the early 2000s. This period is now called the Modern Grand maximum of solar activity. Grand maxima are periods when the sunspot cycles attain very high amplitudes. Presently, the Modern Grand maximum is over, and the sunspot activity level of the on-goingsolar cycle 24 is quite moderate, considerably lower than during the previous cycles forming the Modern Grand maximum.
Since direct sunspot observations only exist for the last 400 years, the occurrence of Grand minima and Grand maxima can be studied only by proxy data, especially the cosmogenic radionuclides 14C and 10Be (see Chapter 2.5).
A recent study, using 14C isotopes measured in tree-rings covering the whole Holocene (Figure1), provides a list of 27 Grand minima and 19 Grand maxima during the last 12 thousand years (Usoskin et al., 2007). Grand minima can
1Sodankyl¨a Geophysical Observatory, Oulu unit, University of Oulu, 90014 Oulu, Finland
2ReSoLVE Center of Excellence, Astronomy and Space Physics Research Unit, University of Oulu, Finland
c
EDP Sciences 2015 DOI: 10.1051/978-2-7598-1733-7.c114
Fig. 1.Sunspot activity reconstructed from 14C data throughout theHolocene. Blue and red areas denote Grand minima and maxima, respectively. The entire series is spread over two panels for better visibility (Modified afterUsoskin et al.(2007)).
be robustly defined and form one distinguishable mode of the solar dynamo (Usoskin et al., 2014). They occur irregularly, which implies that these extreme states in the solar dynamo are driven by a chaotic or stochastic rather than a cyclic process. Thus, their occurrence cannot be reliably and deterministically predicted. However, Grand minima tend to cluster in groups of several minima (as, e.g., Oort, Sp¨orer and Maunder minima in 1200–1700 AD) with roughly 200 years in-between, seem as the so-called Suess or deVries cycle. Clusters are separated by intervals of several millennia. Grand minima seem to divide into two types according to their duration: short minima, such as theMaunder minimum, which last 40–90 years and long minima, like the Sp¨orer minimum, which last 100–170 years.
Grand maxima are more uncertain and cannot be unambiguously defined.
Also, it is not known if Grand maxima form a separate dynamo mode or if they are an extreme part of the normal sunspot distribution. Grand maxima seem to occur irregularly, and without any apparent clustering or periodicity. Their duration varies between 30 and 80 years. The Modern Grand maximum in the 20thcentury was an example of this rare but not exceptional form ofsolar activity.
INFOBOX 2.3
A PRACTICAL GUIDE TO SOLAR FORCING DATA
T. Dudok de Wit1, B. Funke2, A. Sepp¨al¨a3, E. I. Tanskanen3and I. Usoksin4
1 Introduction
The Sun-climate connections that are discussed in this book rely on a large body of observations, which come with their uncertainties, shortcomings and pitfalls.
Knowing these is crucial when it comes to assessing climate impacts.
Here, we provide a non-exhaustive list of solar forcing observables that are most frequently encountered in Sun-climate studies. For each of them, we provide some recommendations as to the data sources, the limitations to consider, etc. This practical chapter is about science in action. Therefore, the information is likely to become obsolete as new measurements are made, or old ones are reinterpreted.
2 Solar forcings
2.1 Total Solar Irradiance (TSI): direct observations
The TSI represents the total solar radiative input per unit surface, at the top of the atmosphere, for a normalised Sun-Earth distance of 1 AU. Historically, the TSI has always been the main, if not the only solar input into the atmosphere, and it remains a key ingredient of the Earth’s energy budget (Trenberth et al., 2009).
Direct and continuous observations of the TSI started in November 1978, and the datasets of interest are composites that are made out of numerous observations. Most instruments agree well on relative variations in the TSI.
They disagree, however, on their long-term evolution, which is still hotly debated.
1University of Orl´eans, France
2Instituto de Astrof´ısica de Andaluc´ıa, CSIC, Granada, Spain
3Finnish Meteorological Institute, Helsinki, Finland
4University of Oulu, Finland
c
EDP Sciences 2015 DOI: 10.1051/978-2-7598-1733-7.c115
The main challenge with the TSI is its extremely small relative variation with the solar cycle (less than 0.7 %), which requires high accuracy measurements.
Only most recent instruments can achieve uncertainties as low as 350 ppm5, and stabilities of the order of 10 ppm/year.
There exist today three reconstructions of the TSI, but the one that shows the best agreement with independent solar irradiance models, is the TSI composite provided by PMOD, in Davos, seeftp://ftp.pmodwrc.ch/pub. Its value atsolar minimumis presently estimated to be 1360.8±0.5 W m−2(Kopp and Lean,2011;
Schmutz et al.,2013). A new composite, which should be endorsed by the scientific community, is expected to come out in 2016.
2.2 Total Solar Irradiance (TSI): indirect observations
No reliable measurements of the TSI exist prior to 1978; however, proxy-based reconstructions have become a powerful alternative for extending the TSI decades to millennia backward in time (Schmidt et al.,2010).
Early reconstructions were based on solar proxies, such as thesunspot number.
However, their connection with the TSI is often too indirect to enable reliable reconstructions, especially when it comes to understanding variations on multi-decadal time scales. Today’s best reconstructions are based on the concentration in natural archives of radioactive isotopes, such as10Be and14C, whose production rate is modulated by galactic cosmic ray flux, and thus by solar activity(Bard and Frank, 2006; Beer et al., 2012). The connection between the TSI and the concentration of these so-calledcosmogenic isotopesinvolves several intermediate physical processes, and thus assumptions. Early reconstructions used an empirical relation between the two to reconstruct the TSI (Steinhilber et al.,2012). More recently, additional physical constraints have been used to refine the reconstruction (Vieira et al., 2011).
Present reconstructions of the TSI bycosmogenic isotopesallow to go back to about 9400 BC. However their time resolution cannot be much lower than about 10 years, hence excluding the observation of the Schwabe cycle. A good start-ing point for publicly available data sets is the National Geophysical Data Cen-ter, see ftp://ftp.ncdc.noaa.gov/pub/data/paleo/climate_forcing/solar_
variability/
2.3 Solar spectral irradiance (SSI): direct observations
The spectrally-resolved solar irradiance (or SSI) is much more relevant for climate studies than the TSI because various wavelengths have differing impacts on the atmosphere(Ermolli et al.,2013), see Chapters4.1and4.2. Unfortunately, direct SSI observations are scarce, highly fragmented in time and in wavelength. In addition, most instruments suffer from degradation.
51 ppm = 1 part-per-million = 0.001 %
T. Dudok de Wit: A guide to data 115
As of today, the only existing SSI composite dataset (DeLand and Cebula, 2008) is not meant to be used for climate studies. In practice, datasets are used on a per instrument basis, with considerable differences between instruments in quality and in coverage. Several datasets are accessible at the LISIRD data center, see http://lasp.colorado.edu/lisird/. A new composite dataset will come out 2016, containing daily observations since 1980, with wavelengths spanning from 10 to 700 nm, seehttp://projects.pmodwrc.ch/solid/.
Several UV proxies have been developed in response to the recurrent need for characterising the solar UV forcing of the atmosphere. Most proxies reproduce the solar variability on time scales of days to months remarkably well; however, their ability to capture long-term trends is uncertain. The solar radio flux at 10.7 cm (the so-calledF10.7 index) is a popularproxyfor the Extreme-UV (below 120 nm). For longer wavelengths in the UV, the core-to-wing ratio of the Mg II line, which is better known as the Mg II index, and the radio flux at 30 cm, are better alternatives.
Daily values of the F10.7 index go back to 1947, and can be downloaded fromftp://ftp.ngdc.noaa.gov/STP/space-weather/solar-data/
solar-features/solar-radio/noontime-flux/penticton/. Daily values of the MgII index are available since 1978 at http://www.iup.uni-bremen.de/gome/
solar/.
2.4 Solar Spectral Irradiance (SSI): model reconstructions
The severe lack of reliable SSI observations has stimulated the development of various models for reconstructing the observations prior to the space age, and/or to fill in observation gaps. All these models rely on solar proxies, such as the sunspot number(going back to 1610), orcosmogenic isotopes(going back farther in time), see Chapters2.5and2.6. While their agreement with direct observations give high confidence in their accuracy for reconstructions made after 1980, there are considerable uncertainties in the SSI before the space age. So, while the TSI is relatively well constrained by solar proxies (see above), the contribution of its individual bands, and in particular of the UV, remains poorly known.
This situation is improving, as new reconstructions are becoming available, based, for example, on historical of solar images (Dasi-Espuig et al.,2014).
The model reconstruction that is most widely used today for climate studies is NRLSSI, seehttp://lasp.colorado.edu/lisird/; in it current version, NRLSSI goes back to 1882. The SATIRE family of models is more accurate for reproducing daily/weekly variations, seehttp://www2.mps.mpg.de/projects/sun-climate/
data.html. The most accurate of them (SATIRE-S) goes back to 1974; other versions go farther back in time, using simplifying assumptions.
2.5 Galactic cosmic rays
The Earth is continuously bombarded by highly energetic particles of extra-terrestrial origin, called cosmic rays, see Chapter 2.3. Cosmic rays consist of
mostly protons, accompanied by a smaller fraction of α-particles and heavier nu-clei up to iron. There is also a tiny fraction of anti-protons. In addition, a small amount of electrons and positrons is also present. On average, the cosmic ray flux at the Earth’s orbit is about 1 particle per cm2 per second. The energy ofcosmic raysmay reach several 1020 eV but the flux of the most energetic particles is very small. The bulk ofcosmic raysoriginates from our Galaxy, and mostly comes from supernova shocks. These are called galacticcosmic rays(GCR). Cosmic rays with the highest energies originate from exotic extragalactic sources.
Although the galactic cosmic ray flux is roughly constant in the interstellar space (at least at the time scale of up to a million years), the cosmic ray flux at Earth is variable because of the modulation of GCR in the Heliosphere. The latter is a region of approximately 200astronomical units across, which is dominated by the solar magnetic field, and by the solar wind (Potgieter, 2013). The flux of GCR is greater during solar minimum, and lower during solar maximum. The level of modulation varies with the energy of the GCR, from several orders of magnitude for 100 MeVparticles down to a few percent at 20 GeV energy, and vanishes at higher energies. In addition, the Earth is shielded fromcosmic raysby itsgeomagnetic field, which provides better shielding in equatorial regions, and no shielding in polar regions. Because of their high energy, GCR can penetrate deep into theatmosphere; they constitute the main source of the atmosphericionisation in thetroposphereandstratosphere.
One of the most complete databases for accessing these data is the World Data Center for Cosmic Rays, see http://center.stelab.nagoya-u.ac.jp/
WDCCR/. Data from European monitors are accessible through the Neutron Moni-tor Database, seehttp://www.nmdb.eu.
While GCR are always present at Earth, there is another sporadic component called solar energetic particles (SEP, sometimes erroneously called solar cosmic rays). These particles, which are of solar origin, mostly consist of protons, and are described below.
2.6 Solar Proton Forcing
During intense solar flares, or when large shock waves cross the interplanetary medium, solar protons can be accelerated up to high energies, giving rise to so-calledsolar proton events. Events with proton energies in excess of 10MeVoccur on average a dozen times per year, and are more frequent when the Sun is active.
A small fraction of these solar particles actually consists of helium, and heavier nuclei. These particle fluxes have been routinely monitored since the 1980s by various geostationary satellites. Sometimes the energy of solar energetic particles can be as high as a severalGeVs so that they can reach the ground level. Such events are called ground level enhancements (GLEs) and occur roughly ten times per solar cycle, with a peak around the maximum and declining phase of the Schwabe cycle.
For studies of solar energetic particles (see Chapters 4.5 and 4.6), the use of solar proton observations from the GOES satellites is strongly recommended.
T. Dudok de Wit: A guide to data 117
These observations have been made readily available by the National Oceanic and Atmospheric Administration (NOAA) and all the existing data can be obtained for example from the Space Physics Interactive Data Resource (SPIDR) online data archive, see http://spidr.ngdc.noaa.gov. A database of GLE events is available athttp://gle.oulu.fi.
For modelling studies wishing to include direct ionisation rates from solar protons formiddle atmospherealtitudes,ionisationrates have been made available by the Solar Influences for SPARC (SOLARIS-HEPPA) activity. Theionisation rates, together with a description of how the data set was produced, and further information on how these can be converted to HOx and NOx production rates (Jackman et al., 2008, 2009), can be found at the SOLARIS-HEPPA homepage (http://solarisheppa.geomar.de), in the Input Data section. At the time of writing, the readily available ionisation rate dataset distributed by SOLARIS-HEPPA covers the years 1963–2013. The use of these ionisation rates for solar energetic particles is highly endorsed by the scientific community. Several of these issues are further discussed bySepp¨al¨a et al.(2014).
2.7 Energetic Electron Forcing
Although energetic electrons are usually measured by the same sets of instru-ments as energetic protons, their origin and their dynamics often differ substan-tially. Most energetic electrons originate from the Earth’s radiation belts, and their energies are typically in the 0.5–10 MeV range. The measurement of en-ergetic electron fluxes is much more challenging than that of enen-ergetic protons, and considerable efforts are presently put into the making of long records, starting with the early observations of 1978.
Precipitating energetic electrons from auroral and radiation belt sources (as described in Chapter4.5) frequently cause enhancedionisationin theatmosphere.
Due to lack of continuous observations (see for example Rodger et al. (2010)), datasets, such as those used for solar protons are currently not available, although alternative approaches are being developed. As these become available they will be included in the above mentioned SOLARIS-HEPPA activity recommended inputs (http://solarisheppa.geomar.de).
As a best estimate for the impact of electron precipitation some models use parameterisations that are based on indices of geomagnetic activity, such as the Kp or Ap index to either describe ionisation (in the case of some models) or NOxproduction (in other models) from electron precipitation. These indices can be obtained, for example, from the SPIDR online data archive (http://spidr.
ngdc.noaa.gov/spidr/). In high top models (models with upper limit in the thermosphere, such as the CESM/WACCM), it is possible to use a parameterisa-tion for thermospheric ionisation from auroral electrons that is based on theKp index (Marsh et al.,2007). For lower top models (models with upper limit in the mesosphere), auroral production of NOx and the subsequent descent from higher altitudes to the model domain can be described as an upper boundary condition.
These boundary conditions are usually semi-empirical, so that they concur with
observations for last decade or so. It should be noted however, that the assumption for the upper boundary condition for NOx production is not ideal for situations where exceptional meteorological conditions are present. This typically occurs dur-ing sudden stratospheric warmdur-ing and elevatedstratopause events (Funke et al., 2014). An example of a semi-empirical Ap-driven NOxupper boundary for mod-els is given by Baumgaertner et al. (2009). An updated Ap-driven NOx upper boundary based on MIPAS observations (Funke et al., 2014) is currently under development and will be made available on the SOLARIS-HEPPA webpage (see above) by the end of 2015.
2.8 Solar wind data
The first samples ofsolar windwere taken in 1959 by Luna spacecraft (Luna 1, 2 and 3) which measured thesolar windion flux by Faraday cups. Since then, the solar windhas been sampled and monitored by a large amount of scientific space-craft, including Mariner (1962), HEOS-1 (1968), ISEE-2 (1977), Ulysses (1990) and SOHO (1995). Continuous solar windmeasurements have been made at the L1 Lagrange point (located between the Sun and Earth), mainly by the Wind (1994) and ACE (1997) spacecraft, both of which are still functional.
Most solar wind spacecraft carry a standard set of instruments that mea-sure proton and electron flux and energy, magnetic field, solar wind composi-tion, temperature, and plasma waves. Each of these reveals a specific aspect of the way the Earth’s environment responds to the varying solar wind, and so the impact of the solar wind cannot be reduced to one single observable.
These datasets are publicly available at the individual mission web sites, such as http://www.srl.caltech.edu/ACE/, and http://wind.nasa.gov/. The most important observables have been merged into composite datasets spanning from the 1970s till today; they are available from the Coordinated Data Analysis Web, CDAWeb (http://cdaweb.gsfc.nasa.gov/), and from the Space Physics Inter-active Data Resource SPIDR (http://spidr.ngdc.noaa.gov/spidr/). Several tools have been developed to locate the spacecraft in the solar wind. One such tool was developed within the International Solar-Terrestrial Physics programme http://pwg.gsfc.nasa.gov/orbits/.
2.9 Geomagnetic data
Thegeomagnetic fieldhas been known to exist since the compass was invented in China around 100 AD. The first multipoint measurements are from the end of 1700s when Alexander von Humboldt first time measured changes of the geomagnetic fieldsimultaneously at the several locations and described the observed changes as geomagnetic storms. Nowadays,geomagnetic fieldmeasurements are produced by hundreds of observatories, research institutes and universities around the globe.
Their data are delivered mainly by individual data producers.
For practical purposes,geomagnetic indices are frequently used instead of di-rect geomagnetic observations. These indices quantify specific properties of the
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T. Dudok de Wit: A guide to data 119