Abstract

We present a new climate data record for total solar irradiance and solar spectral irradiance between 1610 and the present day with associated wavelength and time-dependent uncertainties and quarterly updates. The data record, which is part of the National Oceanic and Atmospheric Administration’s (NOAA) Climate Data Record (CDR) program, provides a robust, sustainable, and scientifically defensible record of solar irradiance that is of sufficient length, consistency, and continuity for use in studies of climate variability and climate change on multiple time scales and for user groups spanning climate modeling, remote sensing, and natural resource and renewable energy industries. The data record, jointly developed by the University of Colorado’s Laboratory for Atmospheric and Space Physics (LASP) and the Naval Research Laboratory (NRL), is constructed from solar irradiance models that determine the changes with respect to quiet sun conditions when facular brightening and sunspot darkening features are present on the solar disk where the magnitude of the changes in irradiance are determined from the linear regression of a proxy magnesium (Mg) II index and sunspot area indices against the approximately decade-long solar irradiance measurements of the Solar Radiation and Climate Experiment (SORCE). To promote long-term data usage and sharing for a broad range of users, the source code, the dataset itself, and supporting documentation are archived at NOAA’s National Centers for Environmental Information (NCEI). In the future, the dataset will also be available through the LASP Interactive Solar Irradiance Data Center (LISIRD) for user-specified time periods and spectral ranges of interest.

A climate data record of daily and monthly solar irradiance values from 1882 to the present, as well as annual values since 1610, is described.

The sun is the dominant energy source for Earth, establishing Earth’s surface temperature, structuring the overlying atmosphere, and powering complex, coupled radiative, dynamical, and chemical processes that produce myriad land–ocean–atmosphere interactions that define our terrestrial habitat. On average, the rate of transport of total radiative energy per unit area that the sun presently provides at the top of Earth’s atmosphere is 1361 W m−2 (Fig. 1). This is the total (spectrally integrated) solar irradiance (TSI, W m−2), which is defined for Earth at a distance of one astronomical unit from the sun. The spectrum of solar irradiance [the solar spectral irradiance (SSI), W m−2 nm−1] that composes the total is similar in shape to a blackbody near 6,000°C (Fig. 1), which is the approximate temperature of the emitting layer of the sun’s lower atmosphere from where more than 99% of the solar irradiance emerges.

Neither the TSI nor SSI is constant despite the historical reference of TSI as “the solar constant.” The sun’s 11-yr, and longer, cycles of magnetic activity driven by a subsurface dynamo alter the amount of magnetic flux that emerges from the solar interior into the sun’s atmosphere, thereby producing solar irradiance variations (e.g., Lean et al. 1998). Sunspots are magnetic features that appear as dark spots on the visible surface of the sun because the enhanced magnetic field strength is sufficient to quell the upwelling energy from the convection zone below. The spots appear dark because they are cooler than the surrounding photosphere (e.g., Rempel and Schlichenmaier 2011). Sunspots can persist on the sun’s surface for several days to weeks; their presence reduces the sun’s irradiance. Bright magnetic features called faculae typically accompany sunspots. Faculae are longer lived and more dispersed over the solar disk than are sunspots. Bright photospheric faculae, which expand into regions called plage in the overlying chromosphere, are hotter than the surrounding solar atmosphere; their presence on the sun’s disk increases irradiance (e.g., Walton et al. 2003).

Changes to the disk-integrated solar irradiance at any time are thus the net of the competing emission enhancements in all bright faculae (and plage) and emission reduction in all dark sunspots. As solar activity increases during the 11-yr cycle, the enhanced facular emission more than compensates for the irradiance reduction in sunspots such that the TSI at solar activity maximum exceeds that at solar minimum (Fig. 2). But on shorter time scales the sun’s rotation, which has an apparent period of approximately 27 days as viewed from Earth, can alter the number of sunspots and faculae on the hemisphere of the solar disk projected to Earth such that there are times when large sunspots reduce irradiance considerably more than the dispersed facular features increase it. Space-era observations of TSI demonstrate, unequivocally, that the sun emits approximately 0.1% more radiative energy at solar maximum than at solar minimum (Kopp and Lean 2011), although TSI decreases in excess of 0.3% can occur on time scales of days to weeks (Woods et al. 2004). Both observations (Harder et al. 2005) and solar atmosphere theoretical models (Fontenla et al. 1993; Solanki and Unruh 1998) indicate that the irradiance spectrum varies as a strong function of wavelength during solar rotation and the solar cycle. Figure 3 shows modeled time series of SSI from 1978 to 2014 binned into four broad wavelength bands spanning the ultraviolet to the near-infrared.

Because of wavelength-dependent absorption and scattering processes the Earth system responds in distinct ways to the sun’s energy inputs in different wavelength regions of the electromagnetic spectrum. The atmosphere completely absorbs solar radiation at wavelengths shorter than 295 nm; this ultraviolet energy both creates and destroys ozone and is a primary determinant of middle atmosphere dynamics and temperature (e.g., Swartz et al. 2012). Longer-wavelength visible and near-infrared radiation penetrates to the troposphere and Earth’s surface where roughly half of the globally averaged incoming solar radiation is absorbed (Trenberth et al. 2009; Stephens et al. 2012). The balance of incident solar radiation that is absorbed or reflected by Earth’s surface and atmospheric components (such as clouds and gases) with the radiation that the earth–atmosphere system emits to space (at infrared wavelengths) defines Earth’s radiation budget (Loeb et al. 2009). Changes in the radiation balance impact the surface temperature and other climate parameters. Solar irradiance, therefore, is designated an essential climate variable1 whose long-term measurement is necessary for the understanding of past and present climate and the projection of future climate (Blunden and Arndt 2014, S30–S32; Bojinski et al. 2014; Holdren 2014).

Determining the sun’s role in climate variability requires uninterrupted records of TSI and SSI that are of sufficient length, consistency, and continuity to be useful for evaluating variations in solar irradiance on a wide range of time scales so as to specify this natural forcing of climate change (Kopp and Lean 2013). The National Oceanic and Atmospheric Administration (NOAA) Climate Data Record program defines a climate data record (CDR) as the sustained and routine generation of products using observational records that span decades to centuries and assigns a “maturity matrix” level to quantify the reliability of a CDR for use in decision-making across many socioeconomic sectors (Bates and Privette 2012). The maturity matrix establishes the transition from basic research to quality-controlled, routinely generated data in these thematic areas: code stability, compliance of metadata with international standards, documentation, product validation, public accessibility to data and code, and utility to a broad user community (Bates and Privette 2012).

The extant database of space-era observations of TSI and SSI (for TSI, 37 yr or approximately three solar cycles and less for SSI) lacks the length and, with respect to SSI, the stability to quantify true solar variability over multiple 11-yr solar activity cycles. Most of the individual observations made thus far have neither sufficiently small uncertainties nor adequate repeatability to achieve the measurement requirements for a climate data record of total and spectral solar irradiance. Table 1 lists these requirements (NPOESS 2002,2): the challenge is to detect variations of less than 0.01% decade−1 in TSI and 0.1%–0.5% decade−1 for SSI that underlie a dominant 11-yr activity cycle of comparable magnitude (NRC 2013). Note that the National Aeronautics and Space Administration’s (NASA) TSIS is expected to meet these requirements with its two instruments, the Total Irradiance Monitor (TIM) and the Spectral Irradiance Monitor (SIM), with each drawing heritage from NASA’s Solar Radiation and Climate Experiment (SORCE) (Rottman 2005; Kopp et al. 2005; Harder et al. 2005), which is still operational and has been acquiring measurements since 2003. In addition to space-based observations of solar irradiance, solar irradiance variability models play a valuable role in constraining the TSI and SSI measurement record, and interpolating and extrapolating over time and wavelength domains to provide past and future irradiance variability estimates over all wavelengths. We present new versions of the Naval Research Laboratory’s (NRL) solar irradiance variability models (Lean 2000; Lean et al. 2005; Lean and Woods 2010)—namely, NRLTSI2 and NRLSSI2 for TSI and SSI, respectively— as a solar irradiance climate data record (the solar irradiance CDR).

The Climate Algorithm Theoretical Basis Document (C-ATBD) for total solar irradiance and solar spectral irradiance (Coddington and Lean 2015) describes in detail the theoretical and operational implementation of the algorithm, including the model inputs, ancillary data, and uncertainty analysis, that is used to estimate the Solar Irradiance CDR with the NRLTSI2 and NRLSSI2 models. In the following section we summarize these elements and illustrate aspects of the Solar Irradiance CDR.

SOLAR IRRADIANCE CLIMATE DATA RECORD ALGORITHM.

NRLTSI2 and NRLSSI2 model formulation.

The calculation of total solar irradiance T(t) and solar spectral irradiance I(λ,t) at a specified time t assumes that the presence on the solar disk of bright faculae and dark sunspots alters the baseline, quiet, total solar irradiance TQ by amounts ΔTF(t) and ΔTS(t), respectively, so that

 
formula

Similarly, the faculae and sunspots alter the baseline solar spectral irradiance IQ(λ) by wavelength-dependent amounts, ΔIF(λ,t) and ΔIS(λ,t), so that

 
formula

where the integrated spectral irradiance equals the corresponding total irradiance such that

 
formula

and the integrated spectral facular and sunspot increments equal their respective contributions to the total solar irradiance:

 
formula

and

 
formula

The algorithm begins by determining indices for the facular brightening, F(t) and sunspot darkening S(t) from ground- and/or space-based observations. Applying scaling coefficients to these indices converts them to corresponding incremental changes in total solar irradiance and solar spectral irradiance (in irradiance units), which are then added to the quiet sun reference values to determine the total solar and spectral solar irradiance at time t. Further details about algorithm flow and operational implementation are provided in the “operational implementation” section below (e.g., Fig. 9).

The spectral irradiance is then partitioned into 3,785 wavelength bins of variable width, designed appropriately for input to general circulation climate models. There are 635 bins of 1-nm width on wavelength grid centers from 115.5 to 749.5 nm, 850 bins of 5-nm width on wavelength grid centers from 752.5 to 4,997.5 nm, 500 bins of 10-nm width on wavelength grid centers from 5,005.0 to 9,995.0 nm, and 1800 bins of 50-nm width on wavelength grid centers from 10,025.0 to 99,975.0 nm.

Adopted quiet sun reference.

The choice of irradiance for the “quiet” (invariant) sun (Fig. 1) is based on measurements from a time period during solar minimum conditions when the solar disk was free of both faculae and sunspots. For TSI, this reference value is 1,360.45 W m−2 and is based on SORCE (Rottman 2005) TIM (Kopp et al. 2005) measurements of total solar irradiance (Kopp and Lean 2011). For SSI, the reference spectrum is obtained as follows: For wavelengths less than 300 nm the spectrum is that of the whole heliosphere interval (WHI) SSI reference spectrum3 garnered from SORCE measurements between 20 March and 16 April 2008 (Woods et al. 2009). For wavelengths between 300 and 1,000 nm the spectral irradiance is that reported from measurements made by the Solar Spectrum (SOLSPEC) instrument on the Atmospheric Laboratory of Applications and Science-1 (ATLAS-1) space shuttle mission (Thuillier et al. 1998) constrained in magnitude to match the overall irradiances of the WHI reference spectrum. The constraining process, which is spectrally dependent, allows for the higher spectral resolution of the SOLSPEC measurements relative to SORCE measurements while maintaining the irradiance levels of the quiet sun WHI spectrum; the scaling adjustments (at most ±5%) are within the absolute uncertainties of the measurements. At longer wavelengths the spectral irradiance is from SORCE SIM (Harder et al. 2005) measurements between 1,000 and 2,400 nm, as incorporated into the WHI reference spectrum, and from the Kurucz (1991) theoretical spectrum for 2,400–100,000 nm. In a final step the spectrum is scaled to make the integral of the quiet sun reference spectrum equal to the adopted quiet sun TSI value (i.e., 1,360.45 W m−2).

Model scaling coefficients.

The model coefficients that scale the input facular and sunspot indices are determined from regression of the indices against SORCE observations4 over the time period from 2003 to 2014: for TSI, observations are from the TIM instrument (version 17 data), and for SSI, the observations, at variable spectral resolution, are from the Solar Stellar Irradiance Comparison Experiment [SOLSTICE; version 13 data; see McClintock et al. (2005a)] for wavelengths between 115 and 309 nm and from the SIM instrument (version 21 data) for wavelengths between 309 and 2,400 nm. The model assumes that the scaling coefficients are time invariant. The consistency of the scaling coefficients (not shown) derived from other records of SSI at ultraviolet wavelengths and TSI in the observational database supports the assumption of time invariance but the lengths of these observational records are too short to establish whether this assumption is valid over a range of solar cycles.

Because the calibrations of the SOLSTICE and SIM instruments are less stable over time than those of the TIM, instrumental trends that are likely present in the SSI measurements (Lean and DeLand 2012) preclude the formulation of reliable models of SSI variability from directly measured SSI observations over long time scales. Instead, a relationship between SSI variability and facular brightening and sunspot darkening is first determined using observations over solar rotational time scales where instrumental trends are minimal, especially in comparison to those over the solar cycle. For each 1-nm bin, the observed SSI and the facular brightening and sunspot darkening indices are detrended by subtracting 81-day running means. Multiple linear regression analysis is then used to determine the wavelength-dependent relationships of the detrended time series.

However, regression coefficients of models developed from detrended SSI time series differ from those developed from direct (i.e., not detrended) SSI observations. This is due in part to the smaller range of facular variability in the detrended time series than during the solar cycle and in part to the “imperfect” natures of the facular brightening and sunspot darkening indices in representing the true sources of irradiance variability. To account for this, we adjust the coefficients obtained from the multiple regression analysis on the rotational time scale (i.e., the detrended SSI time series) to the solar cycle time scale by applying a linear scaling constrained by TSI variability in the following way [see Coddington and Lean (2015) for details]. First, the TSI observations are used to numerically determine ratios of the multiple regression coefficients obtained using direct observations of TSI with those obtained using detrended TSI observations. Second, these ratios are used to adjust the coefficients for SSI variations at wavelengths longer than 295 nm (where faculae and sunspots both modulate solar spectral irradiance) as determined from multiple regression analysis of the detrended SSI time series. The rotational-to-solar-cycle adjustments for the facular and sunspot coefficients are 30% and 6%, respectively. Finally, we apply additional facular and sunspot spectral irradiance corrections to numerically constrain the integrated facular brightening and sunspot darkening components in the spectral irradiance such that they equal their respective total solar irradiance counterparts. The corrections depend on the magnitude of the facular and sunspot indices and are approximately 10%–5% and 5%, respectively, for solar maximum conditions. We note that at any given wavelength, the relative facular brightening and sunspot darkening irradiance contributions are not constrained to match TSI itself; spectral irradiance differs relative to TSI variability in different ways, depending on wavelength, even becoming out of phase (with respect to the TSI solar cycle change) near 1,600 nm where the sunspot darkening contribution exceeds that of the facular brightening.

Model inputs and ancillary data.

Proxy indicators of solar magnetic variability are the principal inputs to the irradiance variability models. When facular brightening and sunspot darkening features are present on the solar disk, the magnitude of the changes in irradiance are determined from a scaling computed from the proxy indices quantifying their magnitude and the model coefficients. Figure 2 shows the individual facular brightening and sunspot darkening components, in irradiance units, for the modeled time series of TSI from 1978 to 2014. In the extant satellite era the proxy of facular brightening on the sun is irradiance (i.e., integrated over the solar disk) measurements of magnesium (Mg) II emission. The Mg II index (Viereck et al. 2001) is the ratio of measurements from the core of the h and k Mg II emission lines5 at 280 nm to measurements in the nearby wings (278 and 282 nm), and variability in the Mg II index is attributed to chromospheric extensions of the photospheric faculae. Since 1978, multiple satellite missions have recorded the Mg II index (Skupin et al. 2005; Viereck et al. 2004; Snow et al. 2014) and future missions will extend the record (Snow et al. 2009). For the Solar Irradiance CDR we utilize the University of Bremen6 Mg II measurement composite.

The proxy of sunspot darkening on the sun is computed from the areas and locations of sunspots on the solar disk on any given day (Allen 1973; Foukal 1981; Lean et al. 1998; Brandt et al. 1994) as reported by the U.S. Air Force (USAF) Solar Observing Optical Network (SOON) sites. For sunspot region information7 prior to 1982 we use Greenwich Observatory observations, which began in 1882.

A third component of irradiance variability is an assumed long-term facular contribution that is speculated (see review in Solanki et al. 2013) to produce the secular irradiance change underlying the solar activity cycle on historical time scales (prior to 1950) including during the Maunder Minimum period of anomalously low solar activity from 1645 to 1715. According to simulations from a magnetic flux transport model (with variable meridional flow) of eruption, transport, and accumulation of magnetic flux on the sun’s surface since 1617, a small accumulation of total magnetic flux and possibly the rate of emergence of small bipolar magnetic regions on the quiet sun (called ephemeral regions) produce a net increase in facular brightness (Wang et al. 2005); the increase in TSI from the Maunder Minimum to the present-day quiet sun is about 0.04% [e.g., Lean et al. (2005); cf. different estimates of TSI from the Maunder Minimum to the present]. For the Solar Irradiance CDR the spectral irradiance changes since 16108 are consistent with the Wang et al. (2005) flux transport simulations and integrate to give the corresponding TSI values.

The increase in total solar irradiance from the seventeenth-century Maunder Minimum to contemporary solar minima is of order 0.6 W m−2. This adopted long-term increase in TSI magnitude is similar to that of the Spectral and Total Irradiance Reconstruction—Telescope era (SATIRE-T) model (Krivova et al. 2010, 2011), but an order of magnitude smaller than the 6 W m−2 increase that Shapiro et al. (2011) suggest. However, Judge et al. (2012) report that comparative solar and stellar data indicate that the Shapiro et al. (2011) estimate is at least a factor of 2 too large. By comparing simulated and observed surface temperatures, Feulner (2011) conclude that the increase in TSI since the Maunder Minimum is less than 1 W m−2, and possibly in the range 0–0.3 W m−2.

Uncertainty estimates.

The Solar Irradiance CDR algorithm calculates time- and wavelength-dependent irradiance uncertainties arising from changes in the input facular brightening and sunspot darkening indices (relative to their minimum values) and the coefficients used to scale the facular and sunspot proxy indices to equivalent irradiance increments. Coddington and Lean (2015; see their Tables 5 and 7) outline the error propagation approach to include the additional uncertainties pertaining to the absolute scale of the reference quiet sun values. Not yet accounted for in the uncertainty analysis are assumptions about the proxy indices’ representations of facular brightening and sunspot darkening; these additional, more complex uncertainties are difficult to quantify and their assessment is ongoing.

Uncertainties in the facular and sunspot proxy indices input to the model are the largest sources of uncertainty in the modeled irradiance variability. When the facular brightening and sunspot darkening contributions are zero, as may occur during minima in solar activity, the error budget reduces to that of the absolute uncertainty of the adopted irradiance of the quiet sun (i.e., the absolute uncertainty reported for the SORCE measurements). But such conditions are not typical and whenever magnetic regions manifest on the solar disk, the uncertainties increase as the components that alter the irradiance from background conditions are estimated. The variability in the sunspot darkening and the facular brightening indices that are input to the algorithm are specified as ±20% relative to their respective solar minimum values (i.e., one-fifth of their solar cycle variability), which is representative of statistical variations among sunspot darkening values derived from the USAF SOON sites.

Verification and validation of model output.

We verify the Solar Irradiance CDR algorithm performance by making a number of numerical comparisons. First, the spectrally integrated modeled SSI is compared with the modeled TSI. On average (over several solar cycles, from 1978 to 2014), the agreement of these two quantities is within 0.015 W m−2 and the standard deviation of their differences is 0.004 W m−2. Second, the spectrally integrated facular brightening and sunspot darkening components of the modeled SSI are compared with their TSI model counterparts. On average, the agreement in the two facular-brightening components is better than 0.014 W m−2 and the standard deviation of their differences is 0.006 W m−2. The agreement of the two sunspot darkening components is within 0.002 W m−2 and the standard deviation of their differences is 0.002 W m−2. Last, we compare the modeled solar irradiance (total and spectral) with observations and other models.

Comparisons of modeled and measured solar irradiance

Comparisons are shown of TSI variability from the NRLTSI2 model with SORCE TIM observations for solar rotation periods in the descending phase of solar cycle 23 (Fig. 4a), the minimum at the beginning of solar cycle 24 (Fig. 4b), and for the duration of the SORCE mission (Fig. 4c). Residual differences are shown in Fig. 4d. Over this time period (of approximately one solar cycle) NRLTSI2 explains 92% of the variability of the SORCE TIM observations with a correlation coefficient of 0.96. The standard deviation of the residuals is 0.1 W m−2 and the slope is 1 part per million (ppm) per year, which indicates that the NRLTSI2 model produces an irradiance record that agrees with the SORCE TIM observations to within their 10 ppm yr−1 estimated repeatability (Kopp and Lean 2011). Facular brightening and sunspot darkening activity were relatively high in late October 2003 and the rapid short-term decrease in TSI evident in Fig. 4a was as large as any TSI change measured in the history of the satellite era. Hence, the irradiance changes over this approximately 2-week period are about as large as we anticipate and the associated uncertainty (see section 2d) in the modeled TSI, on the order of 1000 ppm (0.1%), therefore represents an upper limit to the modeled TSI variability.

Figure 5 compares the modeled SSI from the NRLSSI2 model with SORCE SOLSTICE and SORCE SIM observations in four broad wavelength bands. The comparisons are made over solar rotation (27 day) time scales, for which instrumental effects in the observations are smaller than over the solar cycle. Nevertheless, there is a drift in the SIM observations relative to the NRLSSI2 model, which Lean and DeLand (2012) argue is of instrumental origin. Note that the uncertainties shown in Fig. 5 do not include uncertainty on the SSI absolute scale, estimated to be 2%–3% for the SORCE SOLSTICE observations (McClintock et al. 2005b) and for the SORCE SIM observations below 1,350 nm, increasing to 8% for SORCE SIM observations above 1,350 nm (Harder et al. 2010).

Comparisons of solar irradiance between the new and original model formulations

The newly formulated NRLTSI2 and NRLSSI2 models differ from the original NRL models of solar irradiance variability in several significant ways including the quiet sun reference spectrum (see the “adopted quiet sun reference” section), the records of TSI and SSI observations used in multiple linear regressions to establish the scaling coefficients (see the “model scaling coefficients” section), and in the sunspot and facular proxy indices (see the model inputs and ancillary data section).

The original NRL model of total solar irradiance variability was based on a composite TSI record from 1978 to 2003, which Fröhlich and Lean (2004) constructed using irradiance observations of the sun from different instruments on four separate missions: Nimbus-7 (Kyle et al. 1993), Solar Maximum Mission (SMM) and Upper Atmosphere Research Satellite (UARS; Willson 1994), and the Solar and Heliospheric Observatory (SOHO; Fröhlich et al. 1997). Spectral information for wavelengths less than 400 nm was based on SSI observations by SOLSTICE on the UARS mission from 1992 to 1995 (Lean et al. 1997). Because of the lack of observations of solar irradiance variability at wavelengths longer than approximately 400 nm, theoretical estimates from a solar atmosphere model (Unruh et al. 2000) were used to represent the wavelength dependence of sunspot and facular contributions (Lean 2000; Lean et al. 2005; Lean and Woods 2010).

At the time of the original NRLTSI and NRLSSI models the commonly accepted value of the quiet sun total solar irradiance was 1,365.5 W m−2. The original reference spectrum for the NRLSSI model was an average of SOLSTICE observations during the UARS time period for wavelengths between 120 and 400 nm and observations from the ATLAS-1 shuttle mission (Thuillier et al. 1998) for wavelengths between 401 and 874 nm. At longer wavelengths a theoretical spectrum was used (Kurucz 1991). In a final step the original reference spectrum was scaled such that the integral of the SSI equaled the previously adopted value for the TSI of the quiet sun.

Figure 6 compares NRLTSI2 to the earlier model, NRLTSI, for the same time period of Fig. 2. NRLTSI2 has a lower absolute scale because it was produced directly from the SORCE TIM observations. In addition, NRLTSI2 has about 10% more variability than NRLTSI. Figure 7 compares the solar cycle changes in spectral irradiance estimated by NRLSSI2 (with associated uncertainties) with those estimated by the original NRLSSI model. NRLSSI2 has more variability than NRLSSI at wavelengths between 300 and 400 nm but less variability than NRLSSI at wavelengths between 400 and 600 nm (see Figs. 7c–f).

SOLAR IRRADIANCE DATASETS.

The Solar Irradiance CDR includes a composite observational record of total solar irradiance constructed from space-based radiometer composite records between 1978 and 2014 and TIM observations after the launch of SORCE. The prescribed observational composite is the average of two individual composite records, each constructed separately using different bias corrections and assumptions about the uncertainties and repeatability of the extant solar irradiance database and each first separately normalized to the SORCE TIM absolute scale by regression analysis prior to the averaging. Fröhlich and Lean (1998) describe the Physikalisch-Meteorologisches Observatorium Davos (PMOD) composite and Willson and Mordvinov (2003) present the Active Cavity Radiometer Irradiance Monitor (ACRIM) composite. Then, the subset of the average record that overlaps in time with SORCE TIM is replaced by the TIM observations and the assigned uncertainty is that reported by SORCE TIM. For the period of the record prior to the SORCE TIM epoch, the assigned uncertainties are equal to the differences in the PMOD and ACRIM composites (after their normalization to the SORCE TIM scale) plus an added value of 0.5 W m−2 that is the uncertainty of the SORCE TIM’s absolute scale. The Solar Irradiance CDR TSI observational composite will be extended in the future by appending TIM observations and their uncertainties. Figure 8a shows the Solar Irradiance CDR observational composite and Fig. 8b shows the residual differences from the observational composite and the NRLTSI2 variability model. For the time period spanning 1978–2014 the average standard deviation of the residual difference in the composite observational record and the NRLTSI2 model is 0.24 W m−2.

In the near term, the TSI observational composite will be extended using observations as available from measurements made by the TIM instruments on SORCE and on the Joint Polar Satellite System (JPSS) Total Solar Irradiance Calibration Transfer Experiment (TCTE). The TCTE TSI dataset (data available online at http://lasp.colorado.edu/lisird/tcte/tcte_tsi/index.html) began in late 2013 with the launch of the USAF Space Test Program Satellite-3 (STPSat-3; Woods et al. 2014). The TCTE TIM is a nearly identical copy (i.e., a ground “witness”) of the SORCE TIM instrument, repurposed for quick integration on STPSat-3 following the 2011 launch failure of the Glory satellite that carried a next-generation TIM.

In the longer-term future, the Solar Irradiance CDR will be expanded to include total and spectral irradiance measurements made by the next-generation TIM and SIM instruments scheduled for launch to the International Space Station in August 2017 as the TSIS mission. The TSIS TIM and SIM have been designed, built, and calibrated to meet the measurement requirements necessary for a climate data record of solar irradiance (see Table 1). The TSIS SIM employs three (compared with SORCE SIM’s two) measurement channels to better quantify instrument degradation and related uncertainties. The TSIS instruments have been calibrated in the TSI and Spectral Radiometer Facilities at the Laboratory for Atmospheric and Space Physics at the University of Colorado Boulder (Kopp et al. 2007; Richard et al. 2011), which are the only calibration facilities in the world capable of characterizing TSI and SSI instruments at the power levels and vacuum conditions experienced in flight. Coddington et al. (2013) describe these next-generation TIM and SIM instruments in the TSIS ATBD. In the future, new versions of the Solar Irradiance CDR are expected to accrue from the TSIS observational record of TSI and SSI, which will permit validation and modification, as necessary, of the associations of solar irradiance variability with the facular and sunspot proxy indices.

DELIVERABLES.

LASP creates the Solar Irradiance CDR, updates the record quarterly, and provides the record to the NCEI in Network Common Data Form, version 4 (netCDF4), with accompanying metadata that meets current Climate and Forecast (CF) metadata conventions. The algorithm source code and supporting documentation, as well as the input faculae and sunspot indices, are also delivered as part of the CDR dataset. Table 2 summarizes the delivered products.

Daily and monthly averaged data are provided from 1882 to 2014 and annually averaged data from 1610 to 2014. Preliminary (approximately quarterly) extensions to the Solar Irradiance CDR are transferred to NCEI and ultimately replaced with final products at year’s end.

The Solar Irradiance CDR team provides stewardship of the CDR through a yearly quality assurance document describing the stability of the model inputs and the data record. NOAA’s NCEI9 is the definitive source of the Solar Irradiance CDR, but future capabilities will allow users to also download the data over a user-defined time and spectral range of interest from LASP’s Interactive Solar Irradiance Data Center (LISIRD; http://lasp.colorado.edu/lisird) server.

The NRLTSI2 files include time-dependent uncertainties in the modeled TSI and the data are aggregated as follows: a) daily and monthly averaged TSI are provided in separate files for each year in the period of record and b) annually averaged TSI is provided in a separate single file. The NRLSSI2 files do not include time-dependent uncertainties in the modeled SSI (because of file size considerations) but the data are aggregated similarly as for the TSI. Because users of SSI typically require knowledge of the TSI as a constraint, the NRLSSI2 files also include the modeled TSI and its associated uncertainty.

Also provided as part of the Solar Irradiance CDR are modeled reference spectra at 1-nm spectral resolution that are indicative of varying levels of solar activity: quiet, low, moderate, and high. These reference spectra correspond to appropriate 1-month averages obtained at discrete periods during solar cycle 23: July 2008 for low solar activity, May 2004 for moderate solar activity, and September 2001 for high solar activity. The quiet sun reference spectrum corresponds to that described in the NRLTSI2 and NRLSSI2 model formulation section. An additional spectrum assumed to represent solar radiative output at the time of the Maunder Minimum period of anomalously low solar activity is also provided. These five unique reference spectra are a one-time (i.e., no operational update) delivery.

The composite observational record from 1978 to 2014 (as described in the solar irradiance datasets section), which is also delivered to NCEI as part of the Solar Irradiance CDR package, will be updated quarterly with TIM observations as available. To facilitate validation with independent datasets, the time series of the facular brightening and sunspot darkening proxy inputs are also archived at NCEI, with updates at the same cadence as the solar irradiance files.

OPERATIONAL IMPLEMENTATION.

The flow diagram in Fig. 9 provides an overview of the algorithm processing steps to calculate TSI and SSI at a specified time using procedures that are 100% numerically reproducible given identical sunspot darkening and facular brightening inputs. The data processing system runs as part of LISIRD. Automated daily processing updates the data inputs needed for computing the sunspot darkening and facular brightening indices. A software framework called LaTiS provides a web service interface that the processing code uses to access input data.

Data latency.

The availability of the proxy data used to compute the facular brightening and sunspot darkening indices determines the latency of the updates for the Solar Irradiance CDR. New USAF sunspot data files are expected to accrue weekly with a latency of approximately two weeks. The latency is a result of the organization of the sunspot data files by sunspot group number (i.e., not by calendar date) and the time it takes a sunspot group to appear and then rotate off the solar disk. There is also the potential for data latency with the University of Bremen Mg II composite record.

Operational monitoring and quality flagging.

The quality assurance process is ongoing and utilizes both science analysis and data quality assurance. The Solar Irradiance CDR team oversees this process, which involves regular and careful examination of all solar and proxy data, and assesses the veracity and quality of the data to be released. The quality assurance takes several different forms based on 1) the confidence in the calibration and performance of the instruments providing the solar and proxy observations, 2) comparisons of NRLTSI2 and NRLSSI2 model output with measurements, and 3) an understanding of the sun and its variability based on a broad range of solar models and on multiple solar observations at other wavelengths.

The production system supports both automatic and manual diagnostic statistical analyses of the science products. Deviations from expected or predicted values, flagging of anomalous values, and trending of the sunspot blocking function and facular brightening function relative to independent proxies of solar variability as well as trends in final science values relative to independent models and measurements of solar irradiance are all incorporated into the assessment of the stability in the final science data products. The Solar Irradiance CDR team initially monitors the quality flags in the final science products manually, moving to automating portions of the quality control as the algorithm matures; manual monitoring, particularly of the physical representativeness of the facular brightening function and sunspot darkening indices, will continue to be necessary to some extent.

For example, the relationship between the sunspot area and sunspot number must be monitored to identify a physically plausible “zero sunspot area” that occurs when there are no sunspots (i.e., as can occur during solar minimum conditions) from a physically implausible result of the zero sunspot area that may occur with a missing USAF SOON station record. The sunspot catalog maintained by the Debrecen, Hungary, Heliophysical Observatory10 (Győri et al. 2011) is one independent data source that will be accessed for quality assurance of the sunspot darkening. The veracity of the Mg II index can be approximately assessed through correlation studies (e.g., Lean et al. 2001) with independent chromospheric indices such as the singly ionized calcium (Ca II) K line11 (Donnelly et al. 1994) and by using the F10.7-cm solar radio flux,12 which is an independent proxy of chromospheric variability (with a coronal component) (Tapping 2013).

OUTLOOK.

Solar irradiance is an essential universal input to myriad terrestrial applications and we envisage the Solar Irradiance CDR to be of broad use to industrial, scientific, and government applications including renewable energy, water resources, hydrology, atmospheric chemistry, global climate models, stratospheric and stratospheric-climate models, and community radiative transfer models. Future knowledge gained from the more accurate and stable TSIS instruments will be transferred to the ongoing SORCE and TCTE instrument record so that future Solar Irradiance CDR versions may incorporate altered quiet sun reference levels and model scaling coefficients reflecting revised and ongoing solar irradiance datasets (see the “deliverables” section).

New Solar Irradiance CDR versions may also employ altered facular brightening and sunspot darkening indices derived from the same, or improved, input proxy datasets (e.g., Clette et al. 2015), which are regularly scrutinized by comparison with multiple other related indices. Preliminary comparisons of the NRLTSI2 and NRLSSI2 models with observations suggest that improvements can be made in the models’ representation of the irradiance reduction as a result of sunspot darkening. For example, NRLTSI2 and NRLSSI2 overestimate slightly the reduction in TSI and SSI during times of large sunspot darkening (see, e.g., Figs. 4a and 5). Future work will examine the parameterization of the sunspot contrast with area by calculating different sunspot darkening functions and evaluating their performance in the model formulation. Improvements in the sunspot darkening function will, by necessity, also improve the facular brightening function; this source of improvement to the facular brightening function is independent of the improvements to be gained from a higher-fidelity Mg II composite record (see below).

Future efforts will include expanded and improved uncertainty estimates. This work will take into account uncertainties arising from assumptions in the model formulation, including the representation of the Mg II index for the facular brightening component and the USAF sunspot area and location for the sunspot darkening component. These efforts will also encompass improvements in the quantitative uncertainties in the wavelength dependencies of the sunspot and facular contrasts gained from the improvements in the TSI observational record, as well as the facular brightening and sunspot darkening indices described above.

Activities as part of a European-led collaboration called the Solar Irradiance Data Exploitation (SOLID)13 project will lead to improved composite records of the Mg II index and TSI developed using advanced Bayesian statistical approaches (Dudok de Wit et al. 2014) that define the maximum likelihood values of the Mg II index and TSI from a set of individual measurement records from different instruments that are making observations during the same, or different, periods of time. The Solar Irradiance CDR team plans to utilize these future composite records as an improved facular brightening index and as the (longer) TSI measurement record from which to derive the models’ coefficients.

Further enhancements to the Solar Irradiance CDR include the potential for additional irradiance products such as the solar spectral irradiance at the high spectral resolution needed for fundamental line-by-line calculations of atmospheric heating rates.

Finally, there is the possibility that future research may reflect new understanding of the causes of solar irradiance variability necessitating additional terms in the regression analysis and, perhaps, a different model formulation. Members of the Solar Irradiance CDR team are also part of NASA’s recently formed Solar Irradiance Science Team (SIST). The future research activities described above will be conducted as part of SIST activities and the NOAA CDR program. Coddington and Lean (2015) describe in more detail the enhancements listed in this section and planned improvements to the processing code in terms of exception handling and data quality flagging. Comparisons of the Solar Irradiance CDR with a variety of measurements and other models are under way (O. Coddington et al. 2016, unpublished manuscript).

ACKNOWLEDGMENTS

NOAA funded the development and transition of the Solar Irradiance Climate Data Record. NASA supported the construction of the NRLTSI2 and NRLS2 models as part of the SORCE program. The Solar Irradiance CDR team gratefully acknowledges Anand Inamdar, Philip Jones, and Daniel Wunder of NOAA/NCEI for their assistance in transitioning this climate data record to operations, and Bruce Kindel for his assistance with the MODTRAN5 simulations. We acknowledge three anonymous reviewers, whose comments and suggestions greatly improved the quality of this manuscript.

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Footnotes

1

The 50 Global Climate Observing System (GCOS) essential climate variables (ECVs) are tabulated online (www.wmo.int/pages/prog/gcos/index.php?name=EssentialClimateVariables).

2

A new requirements document, the appendix to the Earth Systematic Missions Program Plan: Program-Level Requirements on the Total and Spectral solar Irradiance Sensor (TSIS) project, is in preparation.

3

The WHI SSI reference spectrum is available online (http://lasp.colorado.edu/lisird/whi_ref_spectra/).

4

The SORCE data collection is publically available online (http://lasp.colorado.edu/home/sorce/data/). The SORCE data used in this study are from the TIM level 3 [L3, version 17 (v17)] dataset (sorce_tsi_L3_c24h_latest.txt) and the combined SSI L3 dataset (sorce_ssi_L3_c24h_0000nm_2413nm_20030301_20130729.txt).

5

The designations “h” and “k” for the Mg II emission line doublet date back to conventions adopted by early solar spectroscopists in naming principal solar features by letter.

6

The University of Bremen’s composite Mg II index is available online (www.iup.physik.uni-bremen.de/gome/gomemgii.html).

7

For the Solar Irradiance CDR, we utilize sunspot information archived by the National Centers for Environmental Information [NCEI; formerly the National Geophysical Data Center (NGDC)]. The record is available online (www.ngdc.noaa.gov/stp/spaceweather.html).

8

Interested users may request from the authors calculations of solar irradiance changes since 1610 that are associated only with the solar cycle (i.e., with no added background component).

9

Datasets, source code, and documentation for NCEI’s Solar Irradiance CDR are available online (for TSI and SST at http://gis.ncdc.noaa.gov/all-records/catalog/search/resource/details.page?id=gov.noaa.ncdc:C00828 and http://gis.ncdc.noaa.gov/all-records/catalog/search/resource/details.page?id=gov.noaa.ncdc:C00899, respectively).

10

Debrecen Photoheliographic Data (DPD) are available online (http://fenyi.solarobs.unideb.hu/deb_obs_en.html).

11

National Solar Observatory Ca II K line data are available online (http://nsosp.nso.edu/node/15).

12

The adjusted value of the 10.7-cm solar radio flux measured from the Dominion Radio Astrophysical Observatory in Penticton, CA, is available online from the National Research Council of Canada (www.spaceweather.ca/solarflux/sx-eng.php).

13

Information about the European SOLID project is available online (http://projects.pmodwrc.ch/solid/).