Daily total column ozone (TCO) measured using the Pandora spectrophotometer
(no. 19) was compared with data from the Dobson (no. 124) and Brewer
(no. 148) spectrophotometers, as well as from the Ozone Monitoring
Instrument (OMI) (with two different algorithms, Total
Ozone Mapping Spectrometer (TOMS) TOMS and differential optical absorption spectroscopy (DOAS) methods),
over the 2-year period between March 2012 and March 2014 at Yonsei
University, Seoul, Korea. Based on the linear-regression method, the TCO from Pandora
is closely correlated with those from other instruments
with regression coefficients (slopes) of 0.95 (Dobson), 1.00 (Brewer),
0.98 (OMI-TOMS), and 0.97 (OMI-DOAS), and determination coefficients (R2) of
0.95 (Dobson), 0.97 (Brewer), 0.96 (OMI-TOMS), and 0.95 (OMI-DOAS).
The daily averaged TCO from Pandora has within 3 %
differences compared to TCO values from other instruments. For the Dobson
measurements in particular, the difference caused by the inconsistency in
observation times when compared with the Pandora measurements was up to
12.5 % because of diurnal variations in the TCO values. However, the
comparison with Brewer after matching the observation time shows agreement
with large
Approximately 90 % of total column ozone (TCO) is found in the stratosphere, and its density peak occurs at altitudes between 20 and 30 km (Liou, 2002; Schott, 2007). This layer is essential to the biosphere as it absorbs harmful solar ultraviolet (UV) radiation. In addition, UV absorption by ozone influences global radiative forcing and climate change over long timescales (e.g., Cho et al., 2003; Martens, 1998; WMO, 2014). Since the depletion of ozone layer was first reported in the 1980s (Farman et al., 1985; Chubachi, 1985), extensive studies have been conducted on its long-term trends (e.g., Stolarski et al., 1991; Harris et al., 1997; Reinsel et al., 1981; Reinsel and Tiao, 1987; Ziemke et al., 2005; Fioletov et al., 2002) with consideration of solar activity (e.g., Angell, 1989; Zerefos et al., 2001; Harris et al., 2003), natural oscillations (Creilsen et al., 2005; Appenzeller et al., 2000), detailed chemical mechanism (e.g., Solomon, 1999), slowdown of ozone depletion in upper stratosphere (e.g., Newchurch et al., 2003; Stolarski and Frith, 2006), detection of ozone hole recovery (e.g., Weatherhead et al., 2000; Reinsel et al., 2005), and recent assessment of physical/chemical cause of ozone layer healing based on the observation studies (Solomon et al., 2016). The concentration of anthropogenic ozone-depleting substances (ODSs) has decreased; consequently, global ozone amounts should return to 1980 levels during the 21st century (e.g., WMO, 2014).
Over several decades, ground-based instruments such as Dobson or Brewer
spectrophotometers have been used widely to obtain stable and highly
accurate long-term measurements of global ozone amounts. The Dobson
spectrophotometer was developed in 1928 by G. M. B. Dobson to measure TCO
levels under clear-sky conditions (Dobson, 1968). TCO values are retrieved
by measuring direct or scattered intensity ratios at two wavelength pairs
that have different absorption features in the UV (A pair: 305.5 and 325.4 nm;
D pair: 317.6 and 339.8 nm; recommended by the World Meteorological Organization (WMO); Komhyr et al., 1980;
Leonard, 1989). Since the Brewer spectrophotometer was developed in the
early 1980s, its automated operation has provided high temporal resolution
observation together with Dobson spectrophotometers (e.g., Brewer, 1973;
Kerr et al., 1985; Kerr, 2010). The measurement principle is similar to that
of the Dobson instrument, but with improved technologies and automated
operation; the Brewer spectrophotometer retrieves data on total UV (TUV),
erythemal UV (EUV), TCO, and aerosol optical depth (AOD) in UV, as well as trace
gases such as NO
Recently, the Pandora spectrophotometer (PAN hereafter) was developed at NASA's Goddard Space Flight Center in 2006 to measure the concentrations of trace gases including ozone (Herman et al., 2009; Cede, 2013). The Pandora is an array detector instrument for simultaneous and continuous observation with wide spectral ranges (Herman et al., 2009). With the advantage of continuous spectral radiance observation with high signal-to-noise ratio, the Pandora spectrometer system is a recently developed ground-based monitoring instrument for trace gases, including total ozone and pollutants, to help understand the process of urban air quality and validation of satellite measurements (Tzortzion et al., 2012). In Seoul and Busan, the Pandora spectrometer was first installed in 2012 for the preparation of the Distributed Regional Aerosol Gridded Observation Networks (DRAGON)-NE Asia campaign and validation for Geostationary Environment Monitoring Spectrometer (GEMS) satellite missions, which is the next geostationary satellite mission of South Korea to measure ozone and its precursors. The Dobson and Brewer spectrophotometers have been operated since 1984 and 1997, respectively, to monitor the TCO.
In this study, the Pandora in Seoul is compared with two independent ground-based and two satellite datasets over a 2-year period from 2012 to 2014. Furthermore, the difference between Pandora and other measurements, and the causes of these differences, are discussed. This paper is organized as follows. Section 2 describes the ground-based and satellite datasets used in this study. Section 3 describes the methodology and results of the comparison together with our analysis and discussion. In addition, high-resolution diurnal variations in the Pandora TCO data are compared with Dobson and Brewer measurements. Finally, our conclusions are summarized in Sect. 4.
The Dobson spectrophotometer (Beck no. 124) is located on the rooftop of the
Science Hall of Yonsei University and has been in operation since 1984, with
its operation automated first in 2005 for total ozone measurements (Cho,
1996; Cho et al., 1989, 2003; Kim et al., 2005). This instrument is a standard
instrument for TCO over Korea as a WMO/GAW site (station no. 252). The
instrument retrieves TCO from the observed UV radiance in direct-sun (DS) and
zenith-sky (ZS) modes three times a day with an air mass factor (AMF) of 2.5. A
DS TCO value measured at noon under clear skies is generally
selected as a representative value; however, a value close to noon or the
ZS measurement can be used instead when DS data from noon are
unavailable. After the automation of the Dobson instrument (in particular,
Q levers, attenuator, R dial, observation, and data processing with test) in
2006, accuracy was improved such that the proportion of data points within a
TCO retrieval methods with respect to instruments.
The TCO accuracy of well-calibrated Brewer measurements is estimated to be about 1 % for direct-sun observations. Nearly 200 Brewer instruments are now operating in about 40 countries (Kerr, 2010). A MKIV version has been in operation at Yonsei University, Seoul, Korea, since 1997 (Kim et al., 2011) and has been regularly calibrated by the official technical support, six times in 7 years from 2004 to 2013 (March 2004, February 2006, October 2007, October 2009, November 2011, August 2013), and the standard lamp tests for wavelength and radiance calibrations have been carried out (Kim et al., 2014). Therefore, the TCO data from the Brewer spectrophotometer were well calibrated during the comparison period. The Brewer spectrophotometer (BRE hereafter) observes the UV wavelength region from 290 to 363 nm with a spectral resolution of 0.5 nm on a horizontal surface (cf. Sabburg et al., 2002). It also measures normal direct UV radiation, which can be used to retrieve TCO using five wavelengths in the UV region (306.3, 310.1, 313.5, 316.7, and 320.0 nm; e.g., Kerr et al., 1985; Kerr, 2002; Kim et al., 2011). The data from the BRE have been used in several previous studies for annual EUV and TUV (Kim et al., 2011) and for AOD at 320 nm (Kim et al., 2014). Normally, the BRE at Seoul observes TCO with intervals of tens of minutes, with two different observation modes, DS and ZS measurements, similar to the DBS. However, the ZS-measured TCO is based on the estimation value by the statistical regression approaches by comparing simultaneous observed TCO from DS and ZS under clear-sky conditions. For this reason, DS-measured TCO is more suitable for the comparison test than those from ZS (e.g., Hong et al., 2014; De Backer and De Muer, 1991; Balis et al., 2007). Although the ZS data are partially used from DBS due to its small observation number, the DS data are fully used from BRE for this analysis.
The OMI on board the Aura satellite has been dedicated to monitoring ozone
and trace gases for air quality and climate studies since 2004. This
instrument detects the molecular absorption of backscattered solar light in
the visible and UV wavelengths (270–500 nm) with a spatial resolution of
13
Daily TCO values for the 2 years from
March 2012 to March 2014 from the following instruments:
A Pandora spectrophotometer (no. 19) is a passive system that measures direct sunlight from 280 to 525 nm
using a UV-sensitive charge-coupled device detector of 2048
An overview of the data selection for comparisons is listed in Table 1 with key
parameters for the TCO retrieval algorithm. From Table 1, the cross section
database and effective temperature for ozone absorption are slightly different
among these ozone instruments. The cross section for ozone absorption is used
as in Bass and Paur (1985) for OMI and DBS, Daumont et al. (1992) for BRE, and
Brion et al. (1993, 1998) and Malicet et al. (1995) (BDM) for PAN. In OMI,
BRE, and DBS, the assumed effective temperature for ozone absorption is also
slightly different. Although the cross section database and retrieval methods
have discrepancies among the different instruments, this study used the
operational TCO value as a reference. Because of limitation in observation
frequency for the DBS and OMI, intercomparison analysis is based on the daily
averaged data. However, as the BRE and PAN observe TCO simultaneously in
several minute intervals, these two instruments can analyze the diurnal
variation in addition. The daily TCO datasets were calculated using the
following methods. For PAN and BRE, only the data obtained from the DS
measurements were averaged to obtain a single representative daily value. For
the PAN data in particular, to avoid errors associated with cloud
contamination and stray-light effects, the data were selected using the
following criteria: root mean square of weighted spectral fitting
residuals
The time series of measurements from the four instruments are shown in Fig. 1 for comparison, which range within 230–500 DU and show similar seasonal variations. These seasonal variations are caused by changes to the Brewer–Dobson circulation in the Northern Hemisphere (Brewer, 1949; Wang et al., 2015; Weber et al., 2003). In addition, Fig. 2 shows similar annual cycles with amplitude of about 0.15 % of the average values for the four different instruments. Maximum and minimum values of 2-year averaged monthly TCO and annual ranges are also shown in this figure. All statistics were derived by the data illustrated in Fig. 1 under the condition that the valid number of daily observations was greater than 10 days per month. In this figure, the largest maximum monthly mean TCO values are from the DBS (i.e., 371.5 DU in April), and the smallest minimum monthly mean TCO values are from the PAN (i.e., 268.9 DU in October). The largest annual range is found in the DBS (101.7 DU), whereas the smallest range is in the BRE (81.3 DU). Larger values of annual range appear for the instruments with few observation numbers, DBS and OMI. The data from DBS and OMI are instantaneous values at a specific time; thus, these may reflect the sudden change of total ozone amounts due to stratosphere–troposphere exchange of ozone in winter and spring (e.g., Hwang et al., 2007; Park et al., 2012). The maximum monthly mean TCO value of the PAN shows the smallest relative difference of 1.54 % with that of the BRE. The minimum monthly mean TCO value of the PAN shows the smallest relative difference with that of the DBS of 0.37 %. The OMD also showed the smallest difference in minimum value from that of the PAN of 0.37 %.
Summary of intercomparison statistics for the 2 years from March 2012 to March 2014.
2-year averaged monthly TCO values, together with the maximum, minimum values, and annual ranges (A.R) from the four instruments over the study period.
Table 2 shows the average, standard deviation, and maximum and minimum values
of the daily TCO data measured by the four instruments, together with the
relative differences among the PAN, DBS, BRE, and OMI data. The largest
maximum and smallest minimum TCO values were 467.1 DU on 10 April 2013 and
238.3 DU on 8 October 2013, respectively, measured by OMT. For the 2-year
average TCO value, the DBS was the largest at 331.9 DU and with a standard
deviation of 38.6. In contrast, the PAN showed the smallest 2-year average
value of 317.2 DU, with a standard deviation of 36.8 DU and a maximum of
436.7 DU on 6 April 2012, and a minimum of 249.2 DU on 7 October 2013.
Figure 3 shows the histograms of all daily TCO data with their maximum frequency
in the bin of 300–350 DU, where PAN provides a reasonable amount of sampling
for the entire TCO ranges compared to other instruments. Based on the
comparison result, the average TCO values of the PAN, DBS, BRE, and OMI
instruments in Table 2 are a reliable representation over the 2-year period
for each instrument. The annual mean TCO values from 2012 to 2014 are the
largest for the DBS (331.9
Histogram of daily TCO values from the four instruments (Pandora, Brewer, Dobson, and OMI (TOMS and DOAS)). Vertical axis (frequency) stands for the number of data in each TCO interval.
Intercomparison of daily TCO values between
Intercomparison of daily TCO values from Pandora with Dobson
Time series of relative differences in daily TCO values from
Pandora and those from
ANOVA table for simple linear regression between the PAN and
In this study, the linear least-squares regression method was used for all
comparison results. To ensure high reliability of comparison results, only
datasets in which complete data are available from all instruments were selected.
To this end, prior to making the comparisons it was necessary to verify the
accuracy of the datasets. Thus, intercomparisons of all available TCO values
obtained from each instrument (except for PAN) were performed for the study
period. As illustrated in Fig. 4, all of the regressions show excellent
agreement, with slopes close to 1 : 1 and coefficient of determination
(
Figure 5 shows scatterplots of the daily TCO from PAN and those from DBS,
BRE, and OMI, together with regression lines within an error
range of
We used a generic analysis of variance (ANOVA) table for simple linear regression
to perform a more detailed analysis of these relationships. ANOVA
tables for the comparisons are presented in Table 3, including the mean
squared error (MSE), standard error (s.e.), and
The relatively small slopes,
According to Herman et al. (2015), both the standard TCO retrievals from DBS
and PAN required a correction using a monthly varying effective ozone
temperature for removing seasonal bias. They also showed that the TCO is dependent on the
effective ozone temperature of
Slope,
Diurnal variations in TCO values retrieved from Pandora for six
randomly selected clear-sky days (cloud amount
Figure 7 shows the instantaneous comparison of TCO data between PAN and BRE
based on their continuous observation, which is the most suitable dataset for
detecting diurnal variation. For the comparison, the time difference between two
instruments is within 5 min. From Fig. 7a, the ratio between PAN and BRE is
0.98, which is the same value based on the daily comparison as shown in Fig. 5b,
with a standard deviation of 0.03. The standard deviation is an order of magnitude
higher than those from the daily comparison. In addition, the slope and
Figure 8 shows the slope and
As mentioned above, the temporal resolution of the PAN is about 2 min, which
allows us to detect diurnal variations of TCO. Figure 9 shows six cases of
diurnal variation for the TCO values measured by the PAN with average,
minimum, and maximum values under clear-sky condition when the cloud amount
is less than
In this study, daily total ozone data measured by the Pandora
spectrophotometer were compared using ground-based and satellite measurements
(DBS, BRE, and OMI) over a 2-year period at Yonsei University, Seoul, Korea.
A linear least-squares regression analysis revealed that the Pandora TCO data
show excellent agreement with other instruments, with slopes close to 1 and
The Pandora spectrophotometer is also useful for measuring diurnal variation of TCO by comparing the real-time data with the BRE. Although TCO values at large SZAs have slightly increasing differences, real-time TCO values also have high levels of confidence in the analysis of diurnal variation. Consequently, daily and real-time total ozone data measured by the Pandora spectrophotometer show high reliability and are expected to improve substantially with the regular, accurate calibration and validation associated with the operational monitoring of trace gases and pollutants. The underestimation of PAN TCO in long-optical-path-length cases in Seoul can be attributed to the enhancement of aerosol scattering and the stray-light effect of the instrument, which is similar to previous comparison studies in Herman et al. (2015) and Zhao et al. (2016). However, detailed reasons for TCO underestimation for large SZAs still require further studies.
For the total column ozone data, the daily representative data for Dobson measurements in Seoul
are available from WOUDC/GO3OS (
The authors declare that they have no conflict of interest.
This research was supported by the GEMS program of the South Korean Ministry of Environment and the Eco Innovation Program of KEITI (2012000160002). Authors appreciate the continuous site operation support of the Dobson and Brewer spectrophotometers at Yonsei University from the Korea Meteorological Administration (KMA). Authors also would like to express appreciation for the valuable satellite dataset from the OMI team. Edited by: Erna Frins Reviewed by: three anonymous referees