Critical assessment of surface incident solar radiation observations collected by SURFRAD, USCRN and AmeriFlux networks from 1995 to 2011

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1 JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 117,, doi: /2012jd017945, 2012 Critical assessment of surface incident solar radiation observations collected by SURFRAD, USCRN and AmeriFlux networks from 1995 to 2011 Kaicun Wang, 1 John Augustine, 2 and Robert E. Dickinson 3 Received 14 April 2012; revised 10 October 2012; accepted 15 October 2012; published 7 December [1] Surface incident solar radiation (R s ) drives weather and climate changes. Observations of R s have been widely used as reference data to evaluate climate model simulations and satellite retrievals. However, few have studied uncertainties of R s observations, especially long term. This paper compares R s from 1995 to 2011 at collocated sites collected by the Surface Radiation Budget Network (SURFRAD), the U.S. Climate Reference Network (USCRN) and the AmeriFlux network. SURFRAD stations have measured separately the diffuse and direct components of R s as well as R s by a pyranometer, while R s was measured by a pyranometer or a net radiometer at the USCRN and AmeriFlux sites. R s can be calculated by summing the diffuse and direction radiation measurements. R s measured by the summation technique was compared those measured by a pyranometer or a net radiometer at collocated sites. Agreement among these four independent R s measurements is good with correlation coefficients higher than 0.98 and an average error (one standard deviation) of about 4% at both hourly and monthly time scales. R s has a large spatial variability at the hourly time scale, even exceeding 100 W m 2 in 6 km. This spatial variability is substantially reduced at the monthly time scale. The two independent measurement systems at the SURFRAD sites agree rather well in annual variability of R s with an average relative standard deviation error of 34%. The errors are 71% and 85% for the USCRN and AmeriFlux sites. Evidently, caution should be taken when using the R s data collected at the USCRN and AmeriFlux sites to study annual variability of R s. Citation: Wang, K., J. Augustine, and R. E. Dickinson (2012), Critical assessment of surface incident solar radiation observations collected by SURFRAD, USCRN and AmeriFlux networks from 1995 to 2011, J. Geophys. Res., 117,, doi: /2012jd Introduction [2] The surface incident solar radiation (R s ) absorbed at the surface drives weather processes through latent and sensible heat fluxes [Wang et al., 2010a, 2010b] and longwave radiation emission [Wang et al., 2005]. It therefore determines the Earth s weather and climate, and its change results in climate and environmental change [Trenberth and Fasullo, 2010]. [3] Since the International Geophysical Year (IGY) ( ), R s has been measured with a pyranometer through 1 State Key Laboratory of Earth Surface Processes and Resource Ecology, College of Global Change and Earth System Science, Beijing Normal University, Beijing, China. 2 NOAA Earth System Research Laboratory, Boulder, Colorado, USA. 3 Department of Geological Sciences, University of Texas at Austin, Austin, Texas, USA. Corresponding author: K. Wang, State Key Laboratory of Earth Surface Processes and Resource Ecology, College of Global Change and Earth System Science, Beijing Normal University, 19 Xinjiekouwai St., Beijing , China. (kcwang@bnu.edu.cn) American Geophysical Union. All Rights Reserved /12/2012JD modern coordinated international monitoring activities. Such observations have suggested a widespread dimming between the 1950s and 1980s [Gilgen et al., 1998] and brightening subsequently following [Dutton et al., 2006; Wild et al., 2005]. These observations of R s have also been widely used to evaluate climate model simulations [Dwyer et al., 2010; Wild, 2009a], evaluate satellite retrievals [Diak et al., 2004; Pinker et al., 2005; Xia et al., 2006; Yang et al., 2008], and develop renewable energy [Myers, 2005]. [4] R s estimated by a commercial pyranometer has an uncertainty of 5% (at 95% confidence level, or twice standard deviation error) for daily values under ideal conditions [Gueymard and Myers, 2008; Reda, 2011; Stoffel and Myers, 2010]. This estimation of R s can have errors from its cosine response [Michalsky et al., 1995] and thermal offset [Ji and Tsay, 2010; Ji et al., 2011]. Poor maintenance of a pyranometer can also cause a large amount of uncertainty [Tang et al., 2011]. Furthermore, change over time of the responsivities of instruments will affect the data if pyranometers are not regularly and properly calibrated, possibly leading to erroneous conclusions such as spurious dimming [Riihimaki and Vignola, 2005; Vignola and Reda, 1998; Wilcox et al., 2007; Wild, 2009b]. 1of8

2 Figure 1. A map of the seven SURFRAD sites (red dots), the three UCSRN sites (green crosses), and the three AmeriFlux sites (blue pentagrams) that are collocated at the SURFRAD sites. The abbreviations of the sites are FPK (Fort Peck), BON (Bondville), DRA (Desert Rock), and GWN (Goodwin Creek). [5] Currently, few studies have addressed the uncertainty of R s observations, especially on longer time scales. Past studies have focused on instrument calibration and comparison, using limited data over short periods [Cess et al., 2000; Michalsky et al., 2011; Myers et al., 2002; Stoffel et al., 2000]. NOAA started the Surface Radiation Budget Network (SURFRAD) in 1993 [Augustine et al., 2000, 2005]. It measures diffuse and direct components of R s (with a shaded pyranometer and a pyrheliometer) according to specifications of the World Climate Research Programme (WCRP) [Ohmura et al., 1998]. Its determination of diffuse radiation is made by blocking out the direct solar beam with a solar tracking ball. This method has a relatively high accuracy for measurement of R s [Gueymard and Myers, 2008]. Its uncertainty may be lower for clear periods near solar noon and greater during cloudy periods. The uncertainty of direct-normal irradiance measurements is on the order of 2% or better with well maintained pyrheliometers. The uncertainty of diffuse measurements is about 5% for well-maintained pyranometers with a low thermal offset (see section 2 for detailed information). This summation technique has been used for highly accurate measurements of R s at WCRP Baseline Surface Radiation Network (BSRN) stations [Ohmura et al., 1998]. [6] The SURFRAD network has provided high-quality measurements of R s from 1995 to 2011 at seven sites across the United States (Figure 1), including an independent backup measure of R s by a single pyranometer. It also provides an assessment as to whether its solar trackers are operating correctly or not. SURFRAD has three sites that overlap with the AmeriFlux network sites and three sites that overlap with the U.S. Climate Reference Network (USCRN) (see also section 2 and Figure 1) sites. The AmeriFlux network was set up in 1996 and the USCRN network started in 2000 ( noaa.gov/crn/#), both providing independent observations of R s from nearly all the same locations as the SURFRAD sites (Figure 1 and Table 1). [7] In summary, there are four independent R s observations at two locations of the SURFRAD, UCSRN and AmeriFlux networks and three at two other sites (Figure 1 and Table 1). These observations provide a unique opportunity to evaluate the observations of R s over a long-term period. In this paper, we analyze the uncertainty of the R s observations at these sites. 2. Data [8] The primary objective of the SURFRAD network is to support satellite programs and climate research with accurate, continuous, long-term measurements of the surface radiation budget over the UNITED STATES [Augustine et al., 2000, 2005]. Currently, seven SURFRAD stations are operating in climatologically diverse regions in the United States. (Figure 1). They measure R s by two independent methods: (1) directly by a pyranometer (model SpectroSun SR-75, see also Table 1) and (2) as the sum of its diffuse and direct components as measured by a shaded pyranometer (model Eppley 8 48) and a pyrheliometer (model Eppley NIP), respectively. [9] The Eppley NIP is a World Meteorological Organization (WMO) first class instrument for the measurement of direct-normal solar radiation. Eppley 8 48 is a WMO second-class pyranometer that lacks thermal offset issues. The Table 1. A Summary of the Collocated Sites and Their Instrument Type for Surface Incident Solar Radiation Measurements Site Network Lat, Lon Instrument Type Instrument Spectral Response Range (mm) Uncertainty at 95% Confidence Level FPK (Fort Peck) SURFRAD 48.31, Global: Pyranometer (SpectroSun SR-75) Diffuse: Pyranometer (Eppley 8 48) Direct: Pyrheliometer (Eppley NIP) Global: 2% to 5% Diffuse: 5 Wm 2 Direct: 2% to 3% USCRN 48.31, Pyranometer (SP Lite) <10% AmeriFlux 48.31, Net Radiometer (Kipp and Zonen CNR1) % Global: 2% to 5% Diffuse: 5 Wm 2 Direct: 2% to 3% USCRN 40.05, Pyranometer (SP Lite) <10% BON (Bondville) SURFRAD 40.05, Global: Pyranometer (SpectroSun SR-75) Diffuse: Pyranometer (Eppley 8 48) Direct: Pyrheliometer (Eppley NIP) AmeriFlux 40.01, Pyranometer (LI-COR LI-200SB) <5% DRA (Desert Rock) SURFRAD 36.63, Global: Pyranometer (SpectroSun SR-75) Diffuse: Pyranometer (Eppley 8 48) Direct: Pyrheliometer (Eppley NIP) Global: 2% to 5% Diffuse: 5 Wm 2 Direct: 2% to 3% USCRN 36.62, Pyranometer (SP Lite) <10% GWN (Goodwin Creek) SURFRAD 34.25, Global: Pyranometer (SpectroSun SR-75) Diffuse: Pyranometer (Eppley 8 48) Direct: Pyrheliometer (Eppley NIP) Global: 2% to 5% Diffuse: 5 Wm 2 Direct: 2% to 3% AmeriFlux 34.25, Net Radiometer (Kipp and Zonen CNR1) % 2of8

3 Figure 2. Hourly surface incident solar radiation (R s ) from four independent measurements collected by the SURFRAD, USCRN and AmeriFlux networks: (1) black line indicates R s calculated from direct and diffuse radiation measurements at the SURFRAD sites, (2) red line indicates R s measured by a pyranometer at the SURFRAD sites, (3) green line indicates R s measured by a pyranometer or a net radiometer at the AmeriFlux sites, and (4) blue line indicates R s measured by a pyranometer at the USCRN sites. Data shown were collected on 13 to 19 July 2006 (days of year ). back-up measurement of R s by SpectroSun SR-75 provides an independent check for sum of direct and diffuse solar radiation at SURFRAD sites. These two independent measurement systems are recommended by the WMO for high-quality R s measurements (ftp://ftp.wmo.int/documents/ PublicWeb/arep/gaw/gaw143.pdf). Calibrations of all SURFRAD R s radiometers are done with cavity radiometers traceable to the World Radiation Reference (WRR). All instruments at the SURFRAD sites are regularly calibrated and maintained (also see for detailed calibration information). [10] The USCRN network was established to monitor climate change in the continental UNITED STATES. Each of its stations are monitored and maintained to a high standard. The instruments are calibrated on an annual basis, and three independent measurements of temperature and precipitation are made to ensure a continuous and accurate record. They measure R s by a pyranometer (model SP Lite) to provide information that allows for correction of observed air temperature data due to solar heating ( The USCRN network has 218 such stations, three of which overlap with SURFRAD sites (Figure 1 and Table 1). The spectral response range of their SP Lite pyranometers is mm, and they are calibrated by comparing their voltage output to the mean output, in W m 2, of the three standard Eppley precision spectral pyranometers (PSP) that were calibrated with cavity radiometers traceable to WRR. [11] The AmeriFlux network has more than 100 stations and provides continuous observations of ecosystem level exchanges of CO 2, water, energy and momentum spanning diurnal, synoptic, seasonal, and interannual time scales [Baldocchi et al., 2001]. Currently, these sites are in North America, Central America, and South America. Its three sites that overlap with the SURFRAD network are shown in Figure 1. They measure R s by a pyranometer (model LI-COR LI-200SB, see also Table 1) at the Bondville (BON) site, and by a net radiometer (model Kipp and Zonen CNR1) at the AmeriFlux sites at Fort Peck (FPK) and Goodwin Creek (GWN) sites. Similar to the SP Lite pyranometer, the spectral response of the LI-COR LI-200SB pyranometer does not include the entire solar spectrum and its reading is scaled to R s in the calibration process (Table 1). [12] The locations of the SURFRAD, AmeriFlux and USCRN sites are virtually the same (within 100 m of each other) with the exception of the AmeriFlux site at Bondville (BON), which is 6 km from the SURFRAD and USCRN sites (Table 1). [13] SURFRAD R s data taken prior to 1 January 2009 are at 3 min resolution, and at 1 min resolution on and after that date. The original data of the AmeriFlux and USCRN networks are at half hour and hourly time resolutions, respectively. All three networks first average their original data into hourly values, from which daily R s is calculated. Monthly averages of R s are derived from daily values. 3. Results 3.1. Uncertainty at Hourly Time Scale [14] We first compared the R s observations at the hourly time scale, using the sum of direct and diffuse radiation at the SURFRAD sites as a reference, as recommended by the World Climate Research Programme [Ohmura et al., 1998]. It is impossible and unnecessary to show all of the hourly data. Figure 2 shows as an example the time series of hourly data for the week of July 2006 (days of year 194 to 200). This period is selected because (1) it was clear (cloud free) at all four locations on days 196 and 197 and (2) all the data were available during the period. Figure 3 shows the differences between hourly R s collected by a pyranometer (or a net radiometer) and the component sum (direct plus diffuse) collected at the SURFRAD sites. Table 2 summarizes the statistical results of the comparisons. [15] The four independent R s observations are in very good agreement at the hourly time scale, with a correlation coefficient larger than 0.99 at all the sites. Using the direct plus diffuse measurements at the SURFRAD sites as a reference, the hourly R s collected by a pyranometer or a net radiometer at the three networks has a standard deviation varying from 1.3% to 7.5%, with an average of 3.9% 2.2%. Previous studies have shown that, under ideal conditions, R s collected by a typical single pyranometer has a standard deviation of 2.5% (or an uncertainty of 5% at 95% confidence level) and R s calculated from diffuse and direct radiation component has a standard deviation error of 1% [Gueymard and Myers, 2008; Reda, 2011; Stoffel and Myers, 2010]. Our results are consistent with these past estimates, indicating all the instruments were well maintained and calibrated. The higher standard deviation error of 14.5% for hourly R s at the AmeriFlux BON site is very likely due to the 6 km separation of the stations and consequent difference in cloud cover [Gueymard and Wilcox, 2011], an error that is substantially reduced for monthly averages (Table 3). [16] Figure 3 shows that the differences among the hourly R s measurements are highly variable and can exceed 50 W m 2 for summer noontime comparisons at all these middle latitude 3of8

4 45 calibration value during the winter and/or at high latitudes will introduce a bias in daily averages. The direct and diffuse measurements do not have this bias. In addition, such thermopile instruments are affected by a thermal offset, which has the largest effect under clear and partly cloudy conditions, partly explaining the differences in R s for the comparisons at hourly time scales. Figure 3. Scatterplots of the differences of hourly surface incident solar radiation (R s ) as a function of hourly R s (direct plus diffuse radiation collected at SURFRAD sites): (1) red dots indicate hourly R s collected by a pyranometer at the SURFRAD network minus hourly R s calculated from direct and diffuse radiation measurements at the SURFRAD sites, (2) green dots indicate hourly R s collected by a pyranometer (or a net radiometer) at the AmeriFlux sites minus hourly R s calculated from direct and diffuse radiation measurements at the SURFRAD sites, and (3) blue dots indicate hourly R s collected by a pyranometer at the USCRN sites minus hour R s calculated from direct and diffuse radiation measurements at the SURFRAD sites. Data shown were collected on 13 to 19 July 2006 (days of year ). sites. R s at the two sites, with the 6 kmseparation,hasa substantial spatial variability more than 100 W m 2. Such variability has an important implication for the evaluation of satellite retrievals and model simulations of R s, which have grid scales on the order of 100 km. [17] The single pyranometer measurements of global irradiance have several problems. In particular, the calibration value applied to all their measurements is determined when the solar zenith angle is at 45, but under clear-sky conditions this calibration actually varies throughout the day. Therefore, although daily integrals of R s may be good if the sun is above and below 45 during the day, the use of the 3.2. Uncertainty at Monthly Time Scale [18] We also compared the four independent R s measurements collected by the SURFRAD, USCRN and AmeriFlux networks at the monthly time scale. Figure 4 shows the time series from 1995 to 2011, and Figure 5 shows scatterplots of the comparisons. Table 3 summarizes the statistical results of the comparisons. [19] The correlation coefficients between the monthly R s measured by a pyranometer or a net radiometer and that calculated from direct and diffuse radiation measurements are higher than 0.98 at all the sites (Table 3). The standard deviation error of monthly R s varies from 1.8% to 9.1%, with an average of 3.8% 2.4%, which is similar to that of hourly R s (3.9% 2.2%, Table 2). Compared to that calculated from direct and diffuse radiation measurements at the SURFRAD sites, R s collected by a pyranometer or net radiometer has an average negative bias of about 1.5%, varying from 0.4% to 3.0% for different sites and type of pyranometer (Table 3) Uncertainty at Annual Time Scale [20] To show the capability of the four R s observations in determining annual variability, we first calculated monthly anomalies from monthly averages by removing its seasonal cycle at each site for each observation. Annual anomalies were calculated from the monthly anomalies. We evaluated the agreement of annual anomalies when data were available. Figure 6 shows the results and Table 4 summarizes the statistical parameters of the comparisons. [21] The relative values in percentage are also shown in Table 4. As for the regular change of solar elevation from hourly to monthly time scales, R s have strong diurnal and seasonal cycles, which are comparable to mean R s. However, annual R s does not has this cycle and its variability is much less than monthly R s. We therefore define a relative bias as follows to quantify our ability in estimating annual variability Table 2. The Statistical Results of Comparisons Between the Hourly Surface Incident Solar Radiation (R s ) Measured by a Pyranometer or a Net Radiometer and That Calculated From Direct and Diffuse Radiation Measurements at the SURFRAD Sites a Site Network Correlation Coefficient Bias Standard Deviation FPK (Fort Peck) SURFRAD (2.5) 24.1 (7.5) USCRN (5.3) 23.3 (5.9) AmeriFlux (2.0) 15.4 (3.7) BON (Bondville) SURFRAD ( 2.0) 8.7 (1.7) USCRN (5.8) 28.2 (6.1) AmeriFlux ( 13.5) 67.4 (14.5) DRA (Desert Rock) SURFRAD ( 0.4) 17.2 (3.1) USCRN ( 3.9) 20.2 (3.9) GWN (Goodwin Creek) SURFRAD ( 0.9) 10.9 (2.1) AmeriFlux ( 2.5) 6.8 (1.3) a The relative values in percentage are also shown. Data shown were collected on 13 to 19 July 2006 (days of year ), as shown in Figures 2 and 3. 4of8

5 Table 3. The Statistical Results of Comparisons Between the Monthly Surface Incident Solar Radiation (R s ) Measured by a Pyranometer or a Net Radiometer and That Calculated From Direct and Diffuse Radiation Measurements at the SURFRAD Sites a Site Network Correlation Coefficient Bias Standard Deviation FPK (Fort Peck) SURFRAD ( 1.8) 4.0 (2.5) USCRN ( 1.8) 8.9 (5.6) AmeriFlux ( 1.7) 6.6 (4.2) BON (Bondville) SURFRAD ( 1.2) 3.0 (1.8) USCRN ( 0.4) 15.0 (9.1) AmeriFlux ( 1.0) 13.2 (8.0) DRA (Desert Rock) SURFRAD ( 0.5) 4.2 (1.8) USCRN ( 3.1) 5.7 (2.4) GWN (Goodwin Creek) SURFRAD ( 0.4) 4.2 (2.3) AmeriFlux ( 1.7) 8.7 (4.8) a The relative values in percentage are also shown in the Table. All the available data from 1995 to 2011 were used, as shown in Figures 4 and 5. of R s. Assuming x1 and x2 are the annual anomalies of R s for comparison, the bias is defined as std(x1) std(x2), and the relative bias is [std(x1) std(x2)]/[std(x1)/2 + std(x2)/2]. The relative standard deviation is defined similarly. [22] Comparison of the component sum of the diffuse and direct radiation measurements with annual anomalies of R s measured by a single pyranometer at the four SURFRAD sites gives an average correlation coefficient of 0.94, and an average standard deviation error of 2.3 W m 2.Asthe annual variability of R s is quite small, the relative standard deviation error is 34% (see Table 4 for detailed information). The agreement between R s measured by a single pyranometer or net radiometer at the three AmeriFlux sites is much worse, with an average correlation coefficient of 0.77, and an averaged standard deviation error of 5.5 W m 2 (71% in relative value). The three USCRN sites are even worse, with an average correlation coefficient of 0.64, a standard deviation error of 5.4 W m 2 (85% in relative value). [23] SURFRAD selected WMO first class and second class instruments to measure R s. The two independent measurements of R s at SURFRAD sites allow a removal of abnormal data due to instrument failure. Our results show that the two independent measurement systems at the SURFRAD sites agree rather well in annual variability of R s, with an average correlation of 0.94, and a relative standard deviation error of 34%. However, agreement between the annual variability Figure 4. Monthly averages of surface incident solar radiation (R s ) from the four independent measurements collected by the SURFRAD, USCRN and AmeriFlux networks: (1) black line indicates R s calculated from direct and diffuse radiation measurements at the SURFRAD sites, (2) red line indicates R s measured by a pyranometer at the SURFRAD sites, (3) green line indicates R s measured by a pyranometer or a net radiometer at the AmeriFlux sites, and (4) blue line indicates R s measured by a pyranometer at the USCRN sites. Figure 5. Scatterplots of the differences of monthly surface incident solar radiation (R s ) as a function of monthly R s (direct plus diffuse radiation collected at SURFRAD sites): (1) red dots indicate monthly R s collected by a pyranometer at the SURFRAD network minus monthly R s calculated from direct and diffuse radiation measurements at the SUR- FRAD sites, (2) green dots indicate monthly R s collected by a pyranometer (or a net radiometer) at the AmeriFlux sites minus monthly R s calculated from direct and diffuse radiation measurements at the SURFRAD sites, and (3) blue dots indicate monthly R s collected by a pyranometer at the USCRN sites minus monthly R s calculated from direct and diffuse radiation measurements at the SURFRAD sites. Data are same as in Figure 4. 5of8

6 Figure 6. Annual anomalies of surface incident solar radiation (R s ) from the four independent measurements collected by the SURFRAD, USCRN and AmeriFlux networks: (1) black line indicates R s calculated from direct and diffuse radiation measurements at the SURFRAD sites, (2) red line indicates R s measured by a pyranometer at the SURFRAD sites, (3) green line indicates R s measured by a pyranometer or a net radiometer at the AmeriFlux sites, and (4) blue line indicates R s measured by a pyranometer at the USCRN sites. of R s measured at the AmeriFlux and USCRN sites to that of the component sum is rather poor, with average relative standard deviations of 71% and 85%, respectively. Therefore, caution should be taken when studying annual variability of these R s measurements. The poor agreement at the AmeriFlux and USCRN sites are partly because these networks use low-grade instruments to measure R s and the spectral response range of their instruments does not cover the whole solar radiation spectrum, which causes greater uncertainty in the broadband measurement. 4. Conclusions and Discussion [24] This study compared R s from 1995 to 2011 collected at four sites of the SURFRAD, USCRN and AmeriFlux networks. The SURFRAD network measures the diffuse and direct components of R s separately along with an independent measurement of R s by a pyranometer, while R s is measured by a pyranometer or a net radiometer at the USCRN and AmeriFlux networks. The agreement among the four independent measurements of R s is quite good, with correlation coefficients higher than 0.98 at both the hourly and monthly time scales for all the sites. The R s measurements have an average error (one standard deviation) of 4% 2% at both the hourly and monthly time scales. This is consistent with previous studies which have shown that, under ideal conditions, R s collected by a typical single pyranometer has a standard deviation error of 2.5% and R s calculated from diffuse and direct radiation component has a standard deviation error of 1% [Gueymard and Myers, 2008; Stoffel and Myers, 2010]. These results indicate that all the instruments for R s measurements were well maintained. [25] However, R s has a large spatial variability at the hourly time scale, which may be more than 100 W m 2 at midday and middle latitudes over a distance of 6 km and has implications for the evaluation of satellite retrievals and model simulations of R s, which have spatial scales of 100 km. This variability is substantially reduced at the monthly time scale. R s collected by a pyranometer or a net radiometer has an average negative bias of about 1.5% (varying from 0.4% to 3.0%) compared to that calculated from direct and diffuse radiation measurements, andislikelycausedbythethermaloffsetofapyranometer. [26] Our results show that the two independent measurement systems at the SURFRAD sites agree rather well in annual variability of R s, with an average correlation 0.94, and a relative standard deviation error of 34%. SURFRAD uses high-quality instruments to measure R s and its diffuse and direct components, with regular calibration and maintenance. In addition, the two independent measurements of R s at SURFRAD sites allow a removal of abnormal data due to instrument failure. [27] It is a challenge to accurately estimate long-term variability, i.e., time scales longer than a year, for the AmeriFlux and USCRN sites. The agreement between annual variability of R s measured at the three AmeriFlux sites (or the three USCRN sites) and those from component sum method are rather poor, with an average relative standard deviation error of 71% (or 85%). Therefore, caution should be taken when using these measurements to study annual variability Table 4. The Statistical Results of Comparisons Between the Annual Anomalies of Surface Incident Solar Radiation (R s ) Measured by a Pyranometer or a Net Radiometer and That Calculated From Direct and Diffuse Radiation Measurements at the SURFRAD Sites a Site Network Correlation Coefficient Bias Standard Deviation FPK (Fort Peck) SURFRAD ( 0.7) 2.7 (30.9) USCRN (12.9) 4.0 (108.4) AmeriFlux (37.9) 1.9 (72.7) BON (Bondville) SURFRAD (2.5) 1.8 (20.3) USCRN (25.4) 9.1 (88.9) AmeriFlux ( 67.6) 12.5 (111.3) DRA (Desert Rock) SURFRAD (16.9) 2.6 (58.0) USCRN ( 22.7) 3.1 (57.0) GWN (Goodwin Creek) SURFRAD (7.0) 2.2 (25.6) AmeriFlux (0.6) 2.1 (29.1) a The relative values in percentage are also shown. Assuming x1 and x2 are the annual anomalies of R s for comparison, the bias is defined as std(x1) std(x2), and the relative bias (in parentheses) is [std(x1) std(x2)]/[std(x1)/2 + std(x2)/2]; the standard deviation is std(x1 x2), and the relative standard deviation (in parentheses) is std(x1 x2)/[std(x1)/2 + std(x2)/2], where std is a function of standard deviation. Please note that the data availability is different for different comparisons (see Figure 6). 6of8

7 of R s. Although USCRN and AmeriFlux instruments are well calibrated and maintained, the annual variability measured at these two networks still have a large or unacceptable uncertainty. The low-grade instruments and their incomplete response spectral range may partly explain the poor performance of annual variability of R s at the AmeriFlux and USCRN sites. [28] R s is not the primary measurement at the AmeriFlux and USCRN stations, and to reduce the cost of that measurement they use lower-grade pyranometers. The spectral response of those pyranometers does not include the entire solar spectrum and their readings are scaled to R s in the calibration process using a triad of standard Eppley PSPs ( However, the scaling coefficient may change with light and meteorological conditions, possibly introducing substantial error in R s measurements by the pyranometer. Previous studies have shown that R s derived from the net radiometer, discussed here (CNR1), may have substantial errors [Blonquist et al., 2009; Brotzge and Duchon, 2000]. [29] Acknowledgments. This study is funded by the National Basic Research Program of China (2012CB955302), the National Natural Science Foundation of China ( ), and the Department of Energy (DE-FG02-01ER63198). Ellsworth G. Dutton is thanked for his helpful comments. We also thank the three anonymous reviewers for their helpful comments. References Augustine, J. A., J. J. DeLuisi, and C. N. Long (2000), SURFRAD: A national surface radiation budget network for atmospheric research, Bull. Am. Meteorol. Soc., 81(10), , doi: / (2000)081<2341:SANSRB>2.3.CO;2. Augustine, J. A., G. B. Hodges, C. R. Cornwall, J. J. Michalsky, and C. I. Medina (2005), An update on SURFRAD: The GCOS surface radiation budget network for the continental United States, J. Atmos. Oceanic Technol., 22(10), , doi: /jtech Baldocchi, D., et al. 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