Limitation of Ground-based Estimates of Solar Irradiance Due to Atmospheric Variations Guoyong Wen, Robert F. Cahalan, and Brent N. Holben For submission to Journal of Geophysical Research Popular summary Solar radiation is the major energy source for Earth’s biosphere. Solar radiation directly affects physical, chemical, and biological processes on the Earth. It is the direct forcing for atmospheric and oceanic circulations, and climate. Understanding this input energy is crucial for understanding the processes of the Earth-atmosphere system. Before the satellite era, solar input energy at the top of the atmosphere, or exo- atmospheric solar irradiance, was estimated from ground-based radiometers using the traditional Langley Plot method in clear atmospheric condition. In Langley Plot analysis, one plots out the “path” that light goes through in the atmosphere and solar irradiance (in logarithmic scale) observed at each time step of observation. When the sky is clear and clean, the plot is nearly a straight line. Then one extrapolates the line to zero “path” to estimate exo-atmospheric solar irradiance. Langley Plot method is named after Samuel P. Langley who introduced this method in early 1900s. This method works perfectly well when atmospheric conditions are absolutely stable (i.e., uniform in space and time). Absolute stable atmospheric condition does not happen in the real world. An example of that is star twinkle in a clear and clean night. The Nature fluctuation of the atmosphere makes the star looks a little brighter or darker when there is little bit less or more molecules and aerosols along the path between the surface observer and the star. Therefore exo-atmospheric solar irradiance can only be estimated by extrapolating a best- fit line to zero “path”. Great efforts were made in the first half of the last century to estimate exo- atmospheric solar irradiance from ground-based radiometers. All attempts failed. Without atmospheric effects, satellite observations of the 1980s and 1990s truly reveal the variations of the solar irradiance with time. It is well known that the variation of the atmospheric conditions has a major impact on the ground-based estimates. But no one has ever quantified such impact. This paper quantitatively describes the relation between uncertainty in the ground-based estimates and the variation of the atmosphere. Then the directly observed solar irradiances from SOLSTICE (Solar Stellar Irradiance Comparison Experiment) on UARS (Upper Atmosphere Research Satellite) are compared with the ground-based estimates from the AERONET site at Mauna Loa for almost two years of data. We conclude the inadequacy of ground-based estimates in monitoring solar variations. The launch of the SORCE (Solar Radiation and Climate Experiment) in January 2003 starts a new era of Sun - Earth climate research. Since variations of solar energy occur on a time scale of decade (or longer), revealing the influence of solar variation on Earth’s climate requires long-term observations from space. Limitation of Ground-based Estimates of Solar Irradiance Due to Atmospheric Variations GUOYONWGE N’ ROBERTF . CAHALAN’,A ND BRENTN . HOLBEN’ Joint Centerf or Earth Systems Technology, Univ. of Maryland Baltimore County and Laboratory for Atmospheres, NASA Goddard Space Flight Center For submission to Journal of Geophysical Reseach (Atmosphere) Joint Center for Earth Systems Technology, U. of Maryland Baltimore County, Maryland. NASA Goddard Space Flight Center, Greenbelt, Maryland Corresponding author address: Dr. Guoyong Wen N ASNGSFC Climate and Radiation Branch Greenbelt. MD 20771 - Authors Dr. Guoyong Wen NASAIGoddard9 13 Greenbelt, MD 20771 (301) 614-6220 (301) 614-6307 (fa) [email protected] Dr. Robert F. Cahalan NASNGoddard913 Greenbelt, MD 2077 1 (301) 614-5390 [email protected] Dr. Brent N. Holben NASNGoddard923 Greenbelt, MD 2077 1 (301) 614-6658 [email protected] ABSTRACT The uncertainty in ground-based estimates of solar irradiance is quantitatively related to the temporal variability of the atmosphere’s optical thickness. The upper and lower bounds of the accuracy of estimates using the Langley Plot technique are proportional to the standard deviation of aerosol optical thickness (- +130(6z)). The estimates of spectral solar irradiance (SSI) in two Cimel sun photometer channels from the Mauna Loa site of AERONET are compared with satellite observations from SOLSTICE (Solar Stellar Irradiance Comparison Experiment) on UARS (Upper Atmospheric Research Satellite) for almost two years of data. The true solar variations related to the 27-day solar rotation cycle observed from SOLSTICE are about 0.15%a t the two sun photometer channels. The variability in ground-based estimates is statistically one order of magnitude larger. Even though about 30% of these estimates from all Level 2.0 Cimel data fall within the 0.445% variation level, ground-based estimates are not able to capture the 27-day solar variation observed from SOLSTICE. 1. Introduction Solar radiation is the major energy source for Earth’s biosphere. Solar radiation directly affects physical, chemical, and biological processes on the Earth. It is the direct forcing for atmospheric and oceanic circulations, and climate. Understanding this input energy is crucial for understanding the processes of the Earth-atmosphere system. The total solar irradiance (TSI) at the mean sun-earth distance (1 AU) had been known as the solar “constant” until satellite observations of the 1980s and 1990s made its variations evident. Before the satellite era, solar irradiance was estimated from ground-based radiometers using the traditional Langley Plot method. Systematic ground-based observations of variability of TSI trace back to the Smithsonian Astrophysical Observatory Solar Constant Program established 100 years 3 ago [Hoyt, 19791. In the first half of the 20” century, a great deal of effort was made to estimate the change of TSI from ground-based measurements and its possible effect on Earth’s climate. Both long-term variations associated with the sunspot cycle [cf. Abbot, 19581, and short term fluctuations over days or weeks [Clayton, 19231 were reported. However, a firm belief that the TSI is invariant was established in some circles [Mitchell, 19651. Efforts were also made to measure the TSI from rocket and high altitude balloons and aircraft in the 1960s and 1970s as reviewed by Willson [1984]. Whether or not TSI is actually constant, or how it might vary, was much debated before satellite observations answered affirmatively. Unaffected by atmospheric effects, only satellite observations truly reveal the variation of TSI associated with magnetic activity of the Sun [Hudson, 1988; Lean, 1997; Willson, 1984; Willson and Hudson, 19911. Variations related to the 11-year sunspot cycle, 27-day solar rotation cycle, and daily variability of solar irradiance have heefi &served 8 vzzriet;l ~f ~gtdites8 s S U E E ~ Xbq~‘ F i5hlkh md T ~ a[n!3 38]. Solar irradiance as a function of wavelength is referred to as “spectral solar irradiance” or SSI. The observations from SOLSTICE (Solar Stellar Irradiance Comparison Experiment) on UARS (Upper Atmospheric Research Satellite) reveal variation of SSI, the amplitude of which depends on the wavelength [Lean, 1997; London et al., 1992; Woods et al., 20001. In the meantime, ground-based radiometers have also undergone great advancement. A worldwide sun photometer network, AERONET, has been established to observe the turbidity of the atmosphere [Holben et al., 19981. Quality assured data sets are available on a daily basis from the AERONET website. The availability of daily observations of 4 exo-atmospheric SSI from satellites, and ground-based estimates of SSI (excluding cloudy days), makes it possible to compare the two directly. The major limitation to the accuracy of ground-based estimates of solar irradiance is the variation of atmospheric optical properties. Much research has been devoted to the study of the effects of the variability of the atmosphere and other factors on the solar irradiance observed by ground-based radiometers [Angstrom, 1970; Shaw, 1976; Shaw, 1983; Reagan et al., 1986; Russell et al., 1993; Schmid and Wehrli, 19951. However, determining how the variability of atmospheric optical properties affects the estimate of SSI in the Langley plot regression analysis is not trivial. In this paper, we revisit the outstanding problem that puzzled pioneer scientists for half a century focusing on quantifying the impact of atmospheric variations on ground-based estimates of SSI. We will show that the uncertainty in ground-based estimates of SSI is theoretically related to the temporal variation of the atmosphere. By comparing the true SSI from SOLSTICE observations and that from ground-based estimates from Mauna Loa for almost two years of data, we will quantitatively demonstrate the inadequacy of ground-based estimates in monitoring solar variations. Data sets used in this study are described in Section 2. Sections 3 presents an analytical relationship between ground-based estimates of SSI and physical quantities. Section 4 compares ground-based estimates of exo-atmospheric SSI in two sun photometer channels from the best AERONET site at Mauna Loa with directly measured values from SOLSTICE. Based on the analytical relation presented in Section 3, Section 5 further presents upper and lower bounds of uncertainty in ground-based estimates of 5 SSI as a function of the variability of the atmosphere. The results are summarized and discussed in Section 6. 2. Data Description We employ daily observations from the SOLSTICE instrument on UARS. The UARS satellite was launched on September 12, 1991 into a near-circular Earth orbit with an inclination angle of 57 degrees to the equator and an altitude near 585 km [Reber et al., 19931. SOLSTICE measures the SSI between 115 and 420 nm with a spectral resolution of 0.1 to 0.2 nm in a daylight orbit. Stellar theory predicts that early- type blue stars are stable in emitting the UV radiation spectrum observed by SOLSTICE. Thus, any change observed for a select group of early-type blue stars is interpreted as instrument degradation, and determine the SOLSTICE instrument transmission over time, providing relative calibration. A detailed description of the SOLSTICE instrument can be found in Rottman et al. [1993] and Woods et al. [1993]. The observing system is estimated to have an absolute error of ~ 3 %and precision of 4%W.it h correction for the drift in transmission, the calibrated SOLSTICE data provide accurate daily average SSI between 119 and 420 nm at an increment of 1 nm [Rottman et al., 19941. We consider ground-based SSI estimates from Cimel sun photometer measurements of AERONET. Started in the early 199os, AERONET is a federated instrument network and data archive program for aerosol characterization [Holben et al., 19981. The Cimel sun photometer of AERONET measures direct transmitted solar irradiance and sky radiance at 340,380,440,500,675,870,940, and 1020 nm with band pass of 2 nm for the 340 nm channel, 4 nm for the 380 nm channel, and 10 nm for the remaining channels. A detailed description of the Cimel sun photometer system is given by Holben 6 et al. [1998]. The Cimel sun photometer is estimated to have an absolute accuracy of -5% and 4%f or precision. The automatic robotic AERONET program has grown rapidly to over 100 sites worldwide. In this study we use data from Mauna Loa, Hawaii. At an altitude of 3397m above sea level in the middle of Pacific Ocean, the site at Mauna Loa Observatory (19’32’N , 155O34’W) is famous for calibrating radiometer instruments, and is perhaps the “clearest” ground site for inferring exo-atmospheric solar irradiance. Even at Mauna Loa, atmospheric conditions are not absolutely stable. The marine inversion layer that traps aerosols is often broken through due to upslope winds as a result of mountain surface heating from solar insolation. When upslope winds bring surface aerosols to higher altitude, more variable atmospheric conditions result buria et al., 1992; Ryan, 1997; Perry et al., 1999; Shaw, 19791. To avoid such variable atmospheric conditions, the Langley Plots are applied to early morning (airmass > 2) measurements of quality asswed Cine! data h this stedy. To examhe whether ground- based estimates could capture exo-atmospheric SSI variation at the time scale of the 27- day solar cycle, every clear day’s data is used. 3. Method The Langley method works perfectly well when the atmosphere is absolutely stable. In reality, the atmosphere experiences constant changes related to dynamics and chemical processes. Number density fluctuations due to turbulence are expected for aerosols in the path between the sun photometer and the Sun. These processes cause temporal variations of aerosol optical thickness and consequently affect estimates of solar irradiance based on the Langley Plot method described below. 7 4 From the Lambert-Beer-Bouguer law, the ground observed direct solar irradiance at any time step i may be expressed as Fj = Foe-m i (q,,+T+6zi ) (1) or In 8 = In& - m,(zm+ Z + hj) (2) where F, is exo-atmospheric SSI, mi is the airmass, zm and 7 are molecular optical thickness (including scattering and gaseous absorption (e.g., 0,, NO,)) and average aerosol optical thickness, respectively, during the time period of observations, and hi is the deviation of aerosol optical thickness from the mean. Rayleigh optical thickness is calculated with input of elevation and optical parameters for a standard atmosphere [Holben et al., 19981. A climatological value is used for 0, [London et al., 19761. Because of its negligible impact on inferred aerosol optical thickness, NO, absorption is ignored [Russell et al., 19931. The variability of molecular optical thickness is effectively embedded in hi.T his is further discussed in Section 6. It is evident that if the atmosphere is absolutely stable ( hj= 0 for every time step), every point (mj,ln&l)ie s in a straight line with intercept In F, and slope -(zm+ 57) in the plot of airmass versus logarithmic solar irradiance. Atmospheric optical properties fluctuate during the observations, and the airmass and the corresponding logarithmic solar irradiance will not strictly follow a straight line. Thus the parameters (Le., intercept and slope) can only be statistically estimated, with inevitable uncertainties. The Langley method finds a best fit linear regression line of the form I ~ F I=n 6 -m(zm +z> (3) 8