The Dutch–Finnish Ozone Monitoring Instrument (OMI) is an imaging spectrograph flying on NASA's EOS Aura satellite since 15 July 2004. OMI is primarily used to map trace-gas concentrations in the Earth's atmosphere, obtaining mid-resolution (0.4–0.6 nm) ultraviolet–visible (UV–VIS; 264–504 nm) spectra at multiple (30–60) simultaneous fields of view. Assessed via various approaches that include monitoring of radiances from selected ocean, land ice and cloud areas, as well as measurements of line profiles in the solar spectra, the instrument shows low optical degradation and high wavelength stability over the mission lifetime. In the regions relatively free from the slowly unraveling “row anomaly” (RA) the OMI irradiances have degraded by 3–8 %, while radiances have changed by 1–2 %. The long-term wavelength calibration of the instrument remains stable to 0.005–0.020 nm.
The Dutch–Finnish Ozone Monitoring
Instrument (OMI) is an imaging spectrograph flying onboard the NASA's EOS
Aura satellite since 15 July 2004. OMI is used to measure atmosphere trace
gases (O
An impression of OMI flying over the Earth. The spectrum of
a ground pixel is projected on the wavelength dimension of the charge-coupled device (CCD; the
columns). The cross-track ground pixels are projected on the swath dimension
of the CCD (the rows). The forward speed of 7 km s
Optical properties for the three channels UV1, UV2 and VIS.
Standard OMI Level 1 data products.
The instrument measures Earth radiances and solar irradiances which are stored in Level 1 products (Sect. 1.1) and used by various Level 2 retrieval algorithms to estimate ozone, trace gases and aerosol properties and UV irradiance. A brief sketch of the optical design (Sect. 2.1) is followed by description of the charge-coupled device (CCD) detectors (Sect. 2.2). Section 3 provides details of the regular calibration routines, including wavelength calibration. A more detailed description of the wavelength registration algorithms is provided in the Appendix. Section 4 describes the basic instrument performance, such as white light and LED calibration sources (Sect. 4.1) as well as long-term changes in the CCDs (Sect. 4.2): gains, electronic offsets, linearity, dark currents, random telegraph noise, bad pixels, signal-to-noise ratio, and pixel response non-uniformity (PRNU). Section 4.3 discusses the approach to the evaluation of and corrections for stray light. The changes in the instrument temperatures and voltages are described in Sect. 4.4 and 4.5. Section 5 concerns the so-called “row anomaly” (RA), its evolution since June 2007, and its impact on the measured radiances. Section 6 provides some basic details of the current (Collection 3) approach to radiometric calibration, and in particular it describes the long-term changes in instrument throughput as observed in solar irradiance measurements performed using a set of diffusers and complemented by measurements of Earth radiances from sites with useful geophysical conditions (e.g., clouds, open-water and ice fields). Section 6 also describes the results of a comprehensive assessment of the instrument transfer function. The conclusions of our study are provided in Sect. 7.
Optical design of the UV channel. The telescope (primary and secondary mirror) is used for both channels. The visible light that passes the dichroic mirror is coupled into the VIS channel. The folding mirror is depicted in two positions (Earth view and Sun/calibration view).
The OMI spectrograph acquires mid-resolution (0.4–0.6 nm) spectra in the
264–504 nm wavelength range. This spectral region is measured by three
instrument channels, UV1, UV2 and VIS (visible; Table 1).
For the UV2 and VIS channel the spectral sampling is 3 pixels for the
full width at half maximum (FWHM). For the UV1 channel this is 1.9 pixel for
the FWHM, which implies that the UV1 channel is undersampled. This is not a
problem for operational use of OMI, because the UV1 channel is mainly used
for ozone profile retrieval, which uses absolute radiances, and does not
rely on spectral fitting. The wide, 115
There are six standard OMI Level 1 data products (Table 2). The products used to generate Level 2 products are generally the global UV and VIS radiance products and accompanying irradiance data. The spatial zoom products are produced 1 day per month. These products zoom in on a smaller swath on ground with a higher spatial resolution. The irradiances are measured once per day. The calibration product provides, for each orbit, the dark-current, background, WLS (white light source) and LED measurements and, whenever applicable (i.e., only at the times of solar calibration), the solar irradiance measurements in different formats, which supplements the standard irradiance output.
Optical design of the VIS channel. The light coming from the telescope (not shown) enters the VIS channel via the mirror from the telescope.
The quality of information in Level 1 data products is a somewhat relative concern from the standpoint of different retrieval applications, since there is considerable variety in the sensitivity of different retrievals to errors and instrument degradation in the Level 1 data. A full review of these sensitivities is beyond the present scope of this paper, but, where appropriate, we summarize them for additional context.
In this section a description of the optical (Figs. 2 and 3) and detector (Fig. 4) design of the Ozone Monitoring Instrument is presented. The Ozone Monitoring Instrument (Levelt et al., 2006; Dobber et al., 2006) is a nadir viewing imaging spectrograph where the UV and visible range of the Earth spectrum is imaged onto two CCD detectors. One dimension of each CCD detector is used for the wavelength measurement, and the other dimension is used for spatial measurement of the cross-track field of view perpendicular to the flight direction. An impression of OMI flying over the Earth surface illustrates the flight and measurement configuration in Fig. 1.
UV CCD detector layout with two wavelength channels, UV1 and UV2. The VIS CCD detector has a similar layout, however, with only one wavelength channel.
The Earth radiances and solar irradiances are acquired through mostly identical optical pathways.
The Earth radiance is imaged via the telescope (primary and secondary mirror) onto the entrance slit. A polarization scrambler is placed in the vicinity of aperture stop and before the secondary mirror of the telescope. The secondary mirror projects images onto the entrance slit of the spectrograph. A dichroic mirror is placed behind the entrance slit and reflects the UV part of the radiance spectrum to the UV channel and transmits the VIS part of the spectrum to the VIS channel. The UV light passes a field lens and then the grating creates the image of the UV spectrum. A mirror splits the UV spectrum in two parts, UV1 and UV2. The UV1 and UV2 channels are split, because the requirements for these channels are different. The UV1 channel is designed to detect the shortest wavelengths. This channel is primarily used for the detection of ozone profiles. The UV signal decreases rapidly for shorter wavelengths, resulting in a low signal-to-noise ratio (SNR). To increase the SNR a design choice was made to increase the detector pixel size, at the expense of spatial resolution. The result is that only 30 spatial channels are available for UV1, versus 60 for UV2 and VIS. Also the choice of coatings on the optical elements is optimized for each spectral channel. Two sets of objective lenses project the spectrum onto the UV CCD detector. In the VIS channel a set of mirrors project the VIS signal onto the grating. The objective lenses project the image of the spectrum onto the VIS CCD detector.
In the irradiance channel the first component the sunlight passes is the optical mesh with 10 % transmission. The sunlight can enter the instrument if the solar aperture mechanism is opened. This is done once per day just before the spacecraft enters into eclipse, at the northern part of the Earth. The sunlight is then reflected by one of the reflection diffusers: quartz volume diffuser (QVD), regular Aluminum or backup Aluminum. These diffusers are mounted on a diffuser carousel. The QVD diffuser is used in daily irradiance measurements. To monitor degradation of the QVD diffuser, the regular Al diffuser is used once per week and the backup Al diffuser once per month. After being reflected by the diffuser, the light can be reflected by the folding mirror (FM), once the mirror is moved to the Sun-observing position, thus blocking the Earth light. After reflection by the folding mirror the optical path is identical for radiance and irradiance. Thus, the difference between the radiance and irradiance optical pathways is the primary mirror for the radiance channel and the reflection diffuser and folding mirror for the irradiance channel.
Schematic optical path. The left panel shows the configuration for Earth radiance measurements. M1 and M2 correspond to the primary and secondary mirrors of the telescope. The middle panel shows the configuration for Sun irradiance measurements, with the folding mirror FM placed between M1 and M2. Sunlight enters the instrument via diffuser D in reflection mode and the FM and M2. The right panel shows the configuration for internal calibration measurements. The light from the white light source passes diffuser D in transmission mode and enters the instrument via FM and M2.
OMI is equipped with two calibration light sources: a quartz tungsten halogen (QTH) white light source and green LEDs. The WLS is imaged via a lens and two mirrors onto a transmission diffuser, which is mounted on the diffuser carousel. When the WLS is used for measurements, the folding mirror is placed in the calibration position. This position will block the Earth radiance. The WLS is used to measure changes in the CCD performance, in particular the pixel-to-pixel response non-uniformity. The WLS can also be used to monitor radiometric throughput. Both the UV and VIS channel are equipped with two green LEDs. These LEDs are placed just before the CCD detector. In the VIS channel the LED light passes directly through the channel objective; in the UV channel the illumination is indirect. The LEDs can be used to monitor the CCD pixel behavior and linearity of the detector and electronics.
The OMI instrument is equipped with two CCD detectors and one electronics
unit (ELU). The CCD detectors in the UV and VIS channel are back-illuminated
UV-enhanced silicon-based CCDs. These detectors (see more details in Dobber
et al., 2006) have 780 (spectral; hereafter designated as column)
Calibration measurements for OMI are performed every day. These comprise solar, background and dark-current measurements as well as the data from dedicated onboard stimuli. The optical paths for radiance, irradiance and calibration measurements are almost identical, except for a few elements (Fig. 5).
For radiance measurements both the primary and secondary mirror, M1 and M2, of the telescope are used. For calibration measurements the folding mirror, FM, is put in the light path between M1 and M2, effectively blocking the Earth shine. Solar light enters the instrument via the diffuser D in reflection mode. Calibration measurements with the internal white light source use almost the same configuration as the solar calibration. The only difference is that the internal calibration light passes through the diffuser in transmission mode. Radiance and calibration pathways comprise the same optical elements, except mirror M1 for radiance and the diffuser D and the folding mirror FM for calibration measurements. Thus, in general these calibration pathways are suitable for calibration and degradation monitoring of all optical elements except mirror M1.
Below we discuss the results of analysis of the L1B and telemetric data performed in three different ways. The Trend Monitoring and Calibration Facility (TMCF; hosted by KNMI, the Netherlands, see TMCF, 2006) performs basic analysis of daily L1B and telemetry data. In the second approach we evaluate the widths, depths and wavelength positions of well-defined absorption features (usually, blends of spectral lines) in the solar and earthshine spectra. Lastly, we analyze long-term trends in the OMI radiances observed over various geographical areas as well as relatively small changes in the daily irradiance measurements. In particular, we pay attention to a sub-set of data acquired over the ice fields of Greenland and Antarctica, i.e., the regions with relatively stable, spatially homogeneous and predictable reflectances.
There are two wavelength registration approaches used in the OMI radiances and irradiances. Hence, the L1B OMI products provide two slightly different wavelength grids. Here we briefly summarize the algorithms, providing more detailed discussion in Appendix A.
During the preflight testing and characterization the wavelength calibration was performed using a PtCrNeAr spectral line source (Dobber et al., 2006). Narrow wavelength windows were centered on prominent spectral lines with accurately known wavelengths: five lines in the UV1 channel, nine UV2 and nine VIS lines. In each window the observed line profile was fitted (in the CCD pixel space) with a Gaussian function in the UV1 channel and a sum of a Gaussian and a flat top function in the UV2 and VIS channels. The fits provided three sets (one per channel) of line-peak positions which were fitted with a fourth-order polynomial and translated into wavelength grids, thus providing the wavelength value for a given CCD pixel (column number).
In-orbit wavelength assignment for radiances and irradiances is done using two methods. In the first approach the wavelength assignment is based on pre-launch and early in-orbit wavelength calibration parameters, i.e., the polynomial coefficients modified as a function of optical bench (OPB) temperature. For the UV2 and VIS channel this function is corrected for wavelength shifts that result from inhomogeneous slit illumination (see more details in the Appendix A). The result is a wavelength map:
Signal change of LED during the mission. Each data point shows a measurement divided by a reference measurement from the beginning of the mission.
For the second method, the wavelength calibration is performed by fitting a reference solar spectrum (Dobber et al., 2008b), an ozone absorption spectrum and a Ring spectrum to measured radiances. The latter two components are excluded from the irradiance fits. The reference spectrum is divided in 8 windows for the UV1 channel, 18 windows for the UV2 channel and 22 windows for the VIS channel. The fits provide a set of wavelengths that are approximated by a polynomial with the corresponding coefficients (similar to Eq. 1) stored in the L1B calibration product. In the original design of the OMI L1B processor, only the parameters based on the first method were stored in the L1B products. These are the standard wavelength calibration parameters predominantly used by Level 2 developers. Later in the mission the wavelength fit parameters were also recorded in the L1B calibration product. Users are advised to implement the wavelength parameters of the first method. Expert users may also benefit from the wavelength fit method, once they find that these parameters are more suitable for a particular L2 application.
The following chapter describes the basic performance of the OMI instrument during 12 years of flight. The basic performance of OMI was monitored using the Trend Monitoring and Calibration Facility (TMCF, 2006). We also developed various trending tools supplementing and extending the basic TMCF metrics.
Signal change of WLS during the mission. Each data point shows a measurement divided by a reference measurement from the beginning of the mission. The three abrupt throughput changes in 2006–2009 are caused by the long (14 min each) WLS duty cycles.
Calibration measurements with the LED are performed once per day and with the WLS once per week. In the analysis of this data the average signal in the OMI channel (UV1, UV2 or VIS) is divided by a reference signal, which is an average signal of that channel at the beginning of the mission. The detected long-term changes in the calibration light sources are summarized in Figs. 6 and 7. These are summaries of the overall changes of the calibration pathway throughput; therefore, it is not possible to distinguish between the degradation caused by the light sources, the optical elements, the detector or the electronic components. The WLS (Fig. 7) shows three abrupt changes in years 2006, 2008 and 2009. This source is used once a week, usually being switched on only for a short duration. So far, the WLS was activated 3 times for about 14 min (cf. the routine 1 min long calibration cycles). Such long duty cycle causes a temperature spike inside the WLS bulb, making the halogen cycle more effective. During these events the intervening tungsten depositories are removed from the inner surface of the bulb, thus increasing the WLS output. There is no explanation for the erratic WLS behavior starting in 2012.
The main purpose of the LEDs is to monitor linearity and CCD detector properties. The observed 15 % decrease in the LED output over the mission time does not impede the calibration routines. The main purpose of the WLS is a monitoring of the CCD detector properties, pixel response non-uniformity (PRNU) inclusive. This source is not used for radiometric calibration. An overall long-term decrease of 10 % in the lamp output as well as the three abrupt increases of the lamp output do not pose any problems for the relevant CCD characterization.
Electronic gain values for different channels and spectral bands.
Gain ratio trends over the mission time for the four gain settings. The very small deviation from 1 for gain setting G1 in the VIS channel (upper left panel) is an indication of the accuracy of the analysis method.
Changes in the electronic offset over the mission time for the four gain settings. Note that offset values for the gain setting G10 and G40 of the VIS channel are not used in radiance measurements.
The OMI CCD detector is proven to be sensitive to cosmic radiation, despite
the
The measured spectrum that comes out of the CCD detector is amplified by the electronics unit. Different parts of the measured spectrum are assigned different electronic gains, thus substantially improving the data quality at the wavelength affected by strong ozone absorption (UV1 and UV2 range in particular). The high-gain parts will then have less readout noise and quantization noise. Both CCD detectors can be divided in four different areas, each with its own gain setting. The gain values for the different channels and spectral bands are shown in Table 3. Absolute gains cannot be measured during the mission but relative gains (the gain ratios) can. The gain ratios are calculated out of a series of LED measurements. Once per month 10 LED measurements are recorded for all four gains, immediately followed by a series of 10 LED measurements with the gain G1 (gain factor equals 1). These 10-exposure series are averaged and then normalized by the G1 average. Then the four areas in the resulting image with different relative gain values are averaged. This results in four relative gain values. The ratio of the measurements with gain setting G1 should be exactly one. In the top left panel of Fig. 8 we see that the ratio is 1.0002 for the VIS channel. This is an indication for the accuracy of the analysis method.
The variations in gain values are not corrected by the L1B processor, hence
they should be accounted for as multiplicative errors of the output signal.
The shown long-term UV gain changes (
Every measurement (radiance, irradiance or calibration) has an electronic offset. The electronic offset is added to the signal to prevent negative values in the amplified signal. Each gain setting has a different offset value. The electronic offset is determined from the first readout in a measurement (the readout register). All readout register measurements from the mission are stored in the TMCF. The electronic offsets are evaluated as follows. In a readout register measurement, all pixels with the same gain value are averaged. Since there is no signal in a readout register measurement, this average equals to the electronic offset for a given gain value.
Non-linearity warnings in output of the CCD amplifiers over the mission time.
Behavior of all offset values during the mission is shown in Fig. 9. We detect the largest variation around 0.5 %. This is accounted for as an additive error and corrected by the L1B processor. Therefore, such changes do not impact Level 2 retrievals. From Fig. 9 it can be seen that the trend in the UV channel differs from the VIS channel. The two channels have individual CCD detectors and supporting electronics, however, of a similar design. Hence, both detectors should show similar temporal behavior. The registered differences remain unexplained. The shown trends are based on standard radiance products, where the gain settings G10 and G40 are not used for the VIS channel. Thus, the VIS data are lacking in the lower panels of Fig. 9.
The output amplifier of the CCD can cause significant non-linearity effects
when the incoming signal produces more than 2e5 electrons (67 % of the
pixel full well). All measurements (radiance, irradiance and calibration)
are corrected for this non-linearity effect by the L1B processor. If the signal
exceeds the 2e5 electrons limit for a certain CCD pixel, a non-linearity
flag will be raised for that pixel. The percentages of pixels with
non-linearity flags are shown in Fig. 10. We
regard the percentage of flagged pixels as reasonably low. It does not
exceed
Once per month linearity measurements with the LED and WLS are performed. For the LED a series of binned measurements with exposure times between 0.1 and 6 s is done. For the WLS the exposure times are between 0.4 and 1.6 s. Analysis of the data has shown that the WLS measurements are not suitable for non-linearity analysis because the WLS shows too much drift during a measurement, up to 1.4 % where the total non-linearity is expected to be around 3 %. The drift of the LED during a measurement is smaller than 0.1 %. The linearity analysis results in curves of deviations from linearity vs. register charge. These curves for a number of samples during the mission are shown in Fig. 11. It can be seen that non-linearity does not vary much during the mission.
Non-linearity comparison for the UV channel for different years. Apart from the 2005/04 curve, the curves are pretty similar, which indicates that non-linearity has not changed much during the mission. The curves for the VIS channel are similar to the UV channel curves.
The average dark currents for two CCDs.
The OMI CCD detectors are operated at
Histograms of dark current measured in the UV channel.
Examples of RTS pixels. The left two columns show results for 2008,
and the right two columns show results for 2015.
Random telegraph signal (RTS) flagging trend over the mission. These results are for unbinned pixels. The binned L1B pixels have flagging rates that are 8 times higher.
The increase in dark current can also be seen in the dark current distribution. Histograms for the UV channel for various years are shown in Fig. 13, along with the UV bad-pixel threshold (see Sect. 4.2.5; when a pixel has a dark-current value above the pre-set threshold, it is flagged as bad by the L1B processor). The corresponding histograms for the VIS channel look similar.
A pixel affected by the random telegraph signal has an average dark current that randomly toggles between two or more levels. Hence, for a given pixel its RTS behavior can be deduced via statistical analysis of the corresponding dark-current levels. This analysis was done on specific dark-current measurements that are performed once a day and employ long integration time in order to improve statistics. There are two different dark-current measurements used in this analysis, with 136 and 2 s integration times, acquired at the same orbit. The measurement with the short integration time is subtracted from the measurement with the long integration time. For each pixel in the resulting image the dark current is calculated by dividing the signal by the difference in exposure times. A series of measurements is taken, belonging to 60 consecutive days. From this dataset the following statistics are calculated for every pixel: mean, variance, observed to expected variance ratio, skewness and kurtosis. Each statistics has pre-set threshold values. If, for a given pixel, one of the statistics exceeds the threshold, it is flagged as an RTS pixel. Examples of a few RTS pixels and their histograms are shown in Fig. 14. The number of pixels that show RTS behavior has increased from 0.1 to 0.7 % over the mission time (Fig. 15).
The results shown in Fig. 15 are for unbinned pixels. Standard radiance and irradiance measurements are performed by binning eight consecutive rows (cross-track direction). If one or more of the eight original (unbinned) pixels carries the RTS warning flag, and then the binned pixel will also carry the RTS warning. Therefore, in the L1B products the number of RTS flagged pixels is 8 times higher than shown in Fig. 15.
Bad-pixel flagging over the mission time for unbinned pixels. The binned L1B pixels have an 8 times higher flagging rate.
Despite the increase observed in RTS on the OMI CCD detectors, the short-lived nature of these events appears to limit their overall impact on the most sensitive Level 2 retrievals. For example in the OMI BrO spectral fitting algorithm (Kurosu et al., 2004), the fitting residuals used for diagnostic purposes grow by less than 5 % over the OMI mission. The same applies to the fitting residuals of the OMCLDRR fitting algorithm (Vasilkov et al., 2008).
Pixels are considered bad if their behavior is perceived as off-nominal.
This can, for instance, be related to the anomalous (either exceedingly high or low)
dark-current readings. Alternatively, bad behavior may be detected via inadequate (either high or low)
response to illumination from a calibration source.
This is
monitored in the TMCF using dark-current, WLS and LED measurements. If
values exceed the absolute threshold limits during dark-current measurement,
the pixel is flagged as bad or dead. The limit values for flagging were
determined in the first years of the mission, in an empirical manner, mostly
based on the dark-current values at that time as well as the notion that
the number of pixels being flagged should be neither exceedingly high nor
too low. The upper limit value for a bad pixel is 2000 el./pix s
The wavelength- and time-binned solar irradiance SNRs for January 2005 (full lines) and January 2016 (dots) in UV1 (black), UV2 (blue) and VIS (red) channels.
The trends in Fig. 16 should be considered in conjunction with the results from Figs. 12 and 13. The dark current of the detectors is increasing (Fig. 12), hence a larger number of pixels is flagged as bad. As in Fig. 15, Fig. 16 shows the unbinned pixels. Therefore, due to binning the amount of the flagged bad pixels in the L1B products is 8 times higher than shown in Fig. 16.
The OMI instrument lacks precisely calibrated, sufficiently stable onboard sources. This makes direct estimation of the signal-to-noise ratio from radiances a very challenging task that is further complicated by earthshine variability stemming from ever-changing geophysical factors. Hence, in order to reveal SNR trends, we revert to the values provided by OMI irradiances as well as specific OMI science products derived from irradiances.
Time-binned (yearly) RMS of the ratios of the solar indices derived from the VIS and UV1 data.
Each daily solar measurement comprises 77 individual exposures taken within
a fairly narrow range of relative (to QVD) solar elevations. We use these
measurements for SNR estimates by choosing all the data within a
Some of the science products turn out to be more sensitive to the gradual SNR decrease. As an example, Fig. 18 shows time-binned (yearly) RMS of the ratios of the solar indices measured in the VIS (Ca II lines) and UV1 (Mg II line) irradiances measured by OMI (Deland and Marchenko, 2013) and the SOlar Radiation and Climate Experiment (SORCE; Snow et al., 2005) on a daily basis. For a particular spectral line (usually, the prominent absorption lines, such as Mg II at 280 nm or H and K Ca II doublet at 393 and 397 nm, respectively), the solar index is defined (see more details in Deland and Marchenko, 2013) as a ratio between the solar flux at the line core to the average solar flux measured at the line's wings. Such indices serve as very sensitive indicators of solar activity, with the lines in question, Mg II and Ca II, changing in almost perfect agreement, however, with the line-profile variability in the Ca II lines being, on average, 5–7 times lower than the relative changes in the Mg II lines. Inspection of the solar Mg II indices provided by OMI and, independently, by SORCE shows no discernible time-dependent trends in the relative noise level (Deland and Marchenko, 2013). This is not surprising, considering the relatively small UV1 SNR changes seen in Fig. 17. Hence, we regard the Mg II values as a relatively noise-free baseline and conclude that the gradual growth of RMS in the ratio of the Ca II and Mg II indices is caused by a steadily increasing instrument noise, with OMI Ca II data being highly susceptible to these changes.
Stray-light warning trend over the mission.
Changes in the normalized line depths of prominent absorption
blends in the solar irradiances observed in UV1
Individual CCD pixels respond differently to incoming light. This is a
detector property that depends on wavelength. This pixel response
non-uniformity is about 5 % for wavelengths around 270 nm and
decreases to 0.1 % for wavelengths around 500 nm. If PRNU is not
corrected properly, it will cause high-frequency structures in the
calibrated L1B output products. To determine PRNU a white light source with
a high spectral stability (up to 10
Various OMI L2 products show different sensitivity to the stray-light
contamination, depending on how the OMI radiances and irradiances are
combined in a specific product. Below we show that in most cases any
long-term trends that may be ascribed to gradual changes in the stray-light
levels do not exceed the achieved
Based on outcome of the preflight tests, the stray-light contamination is modeled in the L1B processor assuming a smooth (low-order polynomial) behavior in the spatial and spectral dimensions. The spatial stray light is measured at the dedicated stray-light rows right below or above the imaging area of each CCD detector: the USA and LSA CCD areas in Fig. 4. The signals from these rows are linearly interpolated over the entire CCD image. The spectral stray-light dependence is evaluated at specific CCD columns, then interpolated at all wavelengths of a channel (UV1, UV2 or VIS) and whenever applicable extrapolated to the wavelengths of another channel. The spatial (row-wise) and spectral (column-wise) stray-light components are combined to form a complete stray-light envelope, which is eventually subtracted from the image. If the stray-light signal is too large (i.e, the corrected radiances turn negative), flags are raised for the corresponding parts of the image. The results of such stray-light flagging are shown in Fig. 19. For the UV1 channel, the one with the highest stray-light warning level (low radiances in the ozone-absorbing domain), there is no significant increase in warnings over the mission time. Considering the potential influence of the row anomaly (see Sect. 5 for more details) on the stray-light estimates, one may conclude that the currently implemented stray-light correction algorithm adequately accommodates such changes in UV1. On the other hand, despite the relatively low level of the flagged events, the VIS channel shows some RA sensitivity: note the rapid increase in flagging at the beginning of 2009 coincident with a major RA event.
Changes in the OPB and the UV channel CCD temperatures.
Row-anomaly evolution for the UV1 and UV2 channels. Black areas show full RA-affected orbits, and gray areas mark partial orbits (northern part). The VIS channel looks similar to the UV2 channel.
Since the described procedure of stray-light removal uses preflight characterization along with some general assumptions about the spatial and spectral stray-light behavior, there is a need for independent estimates of the stray-light contamination. This could be done relying on the Sun as a relatively stable and predictable light source. In order to follow changes in the wavelength registration, as well as spectral line-profile shapes, we select multiple well-developed, relatively deep absorption features (usually, blends of the solar absorption lines) spanning the UV1, UV2 and VIS ranges. In the daily irradiances and in every earthshine spectrum we measure wavelength centroids of the absorption lines, full widths at half maxima and line depths. The line depth and FWHM are related to the radiances coming from the fixed-wavelength, relatively line-free spectral regions in the immediate vicinity of the measured absorption.
Line-profile estimates from the daily irradiance measurements are checked
for
To produce the trends shown in Fig. 20, we
combine all the UV2 and VIS rows, and rows 1–13 from UV1 (reasons for the
latter are discussed below), bin the values over 3 consecutive months, and then
normalize the line depth by the average line-depths values observed during
the latest solar minimum (March 2007–August 2009). Both the line depths
and, to a lesser extent, FWHMs (not shown) of the absorption blends follow
the predictable changes related to the solar cycle (see more details in
Marchenko and Deland, 2014). In essence, practically all absorption lines
in the OMI irradiances are getting progressively shallower with the
gradually (years) increasing solar activity levels. This creates the
inverted-U shapes seen in Fig. 20. The long-term
changes are far more pronounced in the UV1 range compared to VIS, in line
with the expected solar cycle behavior. If there are any instrumental
trends, then at this point they cannot be clearly disentangled from the
anticipated solar-related changes in the UV2 and VIS ranges. The relative
changes (i.e., the deviations from the expected inverted-U shape) in the UV1
line depths point to possible
We also performed (not shown here) line-depth measurements for various
spectral features in the UV2 range of the earthshine spectra. In general,
the earthshine trends conform to the inverted-U shapes seen in the UV2
irradiances (the middle panel in Fig. 20); i.e.,
in radiances the gradual line-depth changes are also mostly driven by the
long-term (years) solar variability. However, we noticed some subtle
deviations from the expected trends, most likely related to gradual
stray-light changes not properly accounted for by the currently adopted
(Collection 3) approach. Considering the measured line-depth values, as well
as magnitudes of the deviations, we assume that such deviations may be
caused by
The temperature of the optical bench impacts the wavelength registration.
The design of the optical bench is such that thermal fluctuations of the
optical bench should have a minimal effect on wavelength registration. In
the OMI case there is a small, however, detectable relation between the two
quantities. The small seasonal variability in the trend in wavelength
registration (see Sect. 6.3) can be directly
related to temperature fluctuations. Besides, the dark-current readings
depend on temperature. In general, when the temperature of the detector
rises by 10
The OMI optical bench is cooled by a passive radiator plate. Without
additional heating the temperature of the OPB would be about 255 K. Passive
heaters warm the OPB to the operational temperature of 264 K. The
temperature of the CCDs is controlled with active heaters in a closed-loop
feedback system. The operational temperature is 265 K, controllable to
The electronics unit monitors a number of internal voltage values. Analysis of the voltage data has shown that fluctuations over the mission are small. The largest fluctuation that was seen in the 5 and 12 volt lines was 0.07 %. There are two voltage parameters that show larger variability. The WLS voltage shows changes up to 0.5 %, and the test voltage changes by 12 %. Since the test voltage is not used for nominal operations, this increase poses no problem for radiances, irradiances and Level 2 product retrieval.
Since June 2007 (the currently accepted date; there are some, though very
limited, indications of an even earlier onset of the anomaly) OMI has
suffered from the so-called row-anomaly (RA) phenomenon. In this anomaly
certain Earth-observing cross-track FOVs (rows) are seemingly blocked,
resulting in abnormally low radiance readings. The most probable cause of
blocking is a partial external obscuration of the radiance port by a piece
of loose multi-layer insulation (MLI) of the instrument itself, but this is
not certain. The first signs of the anomaly were detected in rows 54 and 55
(1-based). These rows remain affected ever since. Since May 2008 the anomaly
affects image rows 38–42 (see Fig. 22). At the
time of writing the anomaly was relatively stable, permanently affecting UV2
rows 25–42 and 54–55, and occasionally spreading to rows 43–53.
Figure 22 depicts the RA evolution in the UV1 and
UV2 channels. The VIS behavior is somewhat similar to UV2, however, showing
different degrees of involvement for the rows in the immediate vicinity to
the main RA domain (defined as rows 25–42). The row anomaly affects the data
in four different ways: Several rows (cross-track viewing angles) have a decrease in signal
strength. This decrease is assumed to be caused by something blocking the
nadir port of OMI. The blockage effect is a multiplicative,
wavelength-dependent factor. Several rows show increased signal level. This increase predominantly
happens in the northern part of the orbit, in apparent relevance to the
incident sunlight. It is assumed that something outside the nadir port is
reflecting sunlight into the instrument. This could be a piece of loose MLI.
This increase in signal level has an additive, wavelength-dependent effect. The partial blocking of the nadir port results in inhomogeneous illumination
of the OMI spectral slit. This causes a slight change in the instrument
spectral response function, changing wavelength registration. Several rows may show increased signal levels at certain parts of orbit.
This is caused by the earthshine from outside of the nominal FOV reflected
into the nadir port. This is an additive factor with time- and FOV-dependent
terms, and thus it is the most elusive row-anomaly effect.
The time-, row- and wavelength-binned, normalized and seasonally
de-trended VIS radiances sampled at all latitudes over the low-reflectance
(
Based on Level 1 data, a daily automatic analysis distinguishes between these four row-anomaly effects. A warning flagging scheme is based on the multitude of parameters provided by such analysis. The most influential contributing factors are the number of negative reflectances, the number of overly large reflectances, the reflectance histogram, the mean-scaled wavelength shift, and the wavelength fit failure count. This flagging scheme is added to the Level 1B product. If the daily analysis results shows significant short-term changes, the flagging scheme is adapted manually. The number of the affected rows has increased since the first appearance of the row anomaly in 2007. Figure 22 shows the affected UV1 and UV2 rows. The VIS channel looks similar to the UV2 channel.
The RA effects grow progressively larger, with pronounced seasonal modulation, in the northern parts of the OMI orbits, when sunlight is coupled into the instrument via the radiance port. Table 3 shows the percentage of rows that is affected for all orbit phases and for the northern parts of orbits, with a noticeable 100 % involvement of the UV1 channel. The row-anomaly effect is not corrected by the L1B processor. The RA flags are included in the affected L1B.
We also performed an independent analysis of the OMI radiances, applying the
following procedure. The typical OMI orbit provides
Percent of data flagged by the two row-anomaly flagging algorithms in use for the UV2 channel. The KNMI algorithm is used to flag the L1B radiance products, while the NASA algorithm is used in several NASA retrieval algorithms to flag the L2 data. Though the physical basis of the two algorithms is rather different, they produce consistent flagging results over the full course of the OMI mission. The presence of high-frequency variations in the NASA flagging algorithm is due to the fact that it flags data dynamically, while the KNMI row-anomaly flags are changed as need determines.
In Fig. 23 we plot the de-trended, binned UV1 and
UV2 radiances for selected rows. The shown rows are very close to the main
row-anomaly area (e.g., mainly image rows 25–42, 54 and 55 in UV2, with
occasional broadening of the row anomaly (RA)-affected area towards image
rows 43–52). These “bordering” rows demonstrate relatively weak reaction to
the on-going RA. Note the dominance of the blocking in the
southern-hemisphere domain, latitude
Figure 24 shows the de-trended row-, altitude- and
wavelength-binned VIS radiances for the low-reflectance (
Percentage of the RA-affected rows, as of August 2014.
A single reliable method for the detection of the row anomaly has proven
difficult to establish because the effects of the anomaly on radiances are
complex and each science algorithm has its own sensitivities to radiance
error that are difficult to capture with a single detection technique. The
KNMI methods for detection through analysis of the OMI L1B radiances
directly worked well to flag bad data from their L2 products but did not
satisfactorily remove affected retrievals in some NASA L2 products.
Therefore, an additional method was developed to determine the affected rows
for the NASA algorithms, which is based on analysis of errors detected in
the NASA TOMS L2 total ozone product. The NASA team developed its own
row-anomaly detection scheme that identifies instrument error using a
statistical analysis of total column ozone error. Total ozone anomalies are
detected using data averaged in 5
The L1B products that are produced are part of the Collection 3 data. Collection 3 data was started on 1 February 2010 with the introduction of version 1.1.3 of the L1B processing software (Ground Data Processing System, GDPS; Dobber et al., 2008a). When version 1.1.3 was introduced, all data since the beginning of the OMI mission has been reprocessed with this version. The main improvements in version 3 are a more elaborate flagging of the row-anomaly effects, new wavelength fit coefficients, improved stray-light correction in UV2, and an improved noise calculation. A one-time adjustment to the radiometric calibration was also applied. There were no changes in the basic flow of corrections on the data products. These corrections are shown in Table 4. More extensive information with, for example, flagging functions can be found in Oord et al. (2006). The generic functions in the table are executed for all measurements. Depending on the measurement type an extra series of correction functions is applied. There has been an effort to make correction functions for the row-anomaly effects, but these corrections did not give the desired results. It is difficult to separate the different row-anomaly effects, and therefore they could not be corrected satisfactorily. There are only flagging functions for the row-anomaly effects.
Correction functions for the different measurement types. Generic corrections are applied to all measurement types.
Relative solar signal of the UV1 channel over the mission. Each data point shown for the three diffusers is a result of a spectral and spatial average over the entire channel. The higher rate of signal change from the frequently used QVD suggests degradation in diffuser reflectivity caused by solar exposure.
The wavelength-binned and normalized QVD solar irradiances for
different rows in the UV1
This section addresses changes in instrument radiometric calibration as observed in the solar measurements and the Earth radiance measurements. Each observational port may provide an independent view of sensor changes since launch that may not be necessarily consistent. This is particularly true for OMI, where the optical paths differ for Earth-view and solar measurements. The challenge is to reconcile these differences and to describe as accurately as possible the calibration changes in the Earth radiance path. We begin with a discussion of the solar measurements.
Solar calibration measurements are performed every day. In a solar calibration measurement the sunlight passes via the mesh through the opened solar aperture onto a reflective diffuser: either the aluminized fused silica (QVD hereafter), or two pure Aluminum diffusers. The reflected sunlight is coupled into the instrument telescope via the folding mirror (see Fig. 5).
The relative solar signal in the UV1 channel for the three diffusers is shown in Fig. 26. In this figure a solar measurement is divided by a reference solar measurement from the beginning of the mission. The average of this ratio for the UV1 channel is calculated and shown in the figure. If we assume the three react similarly to solar exposure, their differences appear to be related to their frequency of exposure. The QVD is used every day, the regular Al diffuser once per week, and the backup Al diffuser once per month. This leads to less degradation of the aluminum diffusers. The changes observed in all channels are provided in Table 5. For the UV1 channel, the signal change is 6 % for QVD, 3 % for regular Al and 2.5 % for backup Al. These are overall signal changes of the complete instrument. Since the backup diffuser is used so little, the signal change of 2.5 % can be attributed to the complete instrument.
The fractional change in the QVD diffuser per hour of solar exposure relative to the regular and backup Al diffuser.
To further substantiate our hypothesis of QVD optical degradation, we zoom in
into individual wavelength bands in Fig. 27. The
bands with the shortest wavelengths have the largest degradation. An
exception to this is the 372–376 nm band in UV2 (not shown), which tends to
degrade slightly (by
We attribute the accelerated degradation of row 20 in UV1 starting in 2009 to scattered sunlight during northern hemisphere Earth-view measurements. This is described as the solar contamination effect in Sect. 5. Assuming this is the cause, the change is likely occurring in the telescope assembly. This follows because the diffusers, as well as the folding mirror, are not in the optical path during Earth-view measurements (Fig. 5); hence, they are not exposed to the anomalously scattered solar light. The primary telescope mirror is bypassed for the solar measurements, so the row 20 anomaly in Fig. 27 is likely caused by accelerated degradation of the secondary telescope mirror. We surmise that the degradation of the primary mirror is even greater for the RA-affected across-track positions since it is the first optical element exposed to the RA-scattered solar light. The interference with other row-anomaly effects makes it impossible to verify this hypothesis.
We can isolate the optical degradation of the solar diffusers by comparing
the signal changes observed with each one. Figure 28 shows the fractional change in the QVD per hour of solar exposure
relative to the other two diffusers. The close agreement between QVD changes
derived from the regular and backup diffusers is an indication that neither
has degraded significantly. If we assume the regular and backup diffusers have similar
degradation rates, the former should be degraded more than the latter in a
ratio of
The annual signal change rates (QVD diffusor, squares) derived
from the wavelength-binned solar irradiances for 2007–2009 (see more details
in Marchenko and Deland, 2014) and fitted with linear polynomials (red
lines) for each OMI channel. Filled circles and
Closer examination of regular diffuser change relative to the backup reveals
a rate of 1.10
The observed QVD degradation rates are similar to those seen for several of the SBUV2 instruments, though the OMI QVD appears to have a steeper wavelength dependence. It is noteworthy that the OMI solar measurements employ a protective mesh in front of the diffuser that attenuates the incident solar irradiance by approximately a factor of 10. This implies that the QVD degradation rate per equivalent solar exposure is much larger than that of the SBUV2 diffusers and larger even than that of the TOMS diffusers (see Jaross et al., 1998). The design and operational factors affecting degradation rates are complex and to this day not fully understood. This underscores the importance of maintaining low exposure frequencies until on-orbit rates become clear.
Measured daily mean radiances in UV2 at 360 nm over Antarctica (black) and Greenland (green) are shown as a function of time relative to initial measurements in 2004. Left panel shows results in row 3, which is at the western edge of the OMI swath and is far from the row-anomaly-related blockage. Right panel shows results for row 33, which is near nadir and is affected by RA.
Trends in monthly mean ratios of OMI radiances measured at 340
and 354 nm on the UV-2 detector (black) and 354 and 380 nm on the VIS
detector (red) for three detector rows. The observed trend in these
Earth-view measurement ratios is < 0.5 % per decade in both
channels. Detector rows 6, 22, and 56 shown here are among those which are
unaffected by the row anomaly. The data shown here were selected to minimize
geophysical effects of wavelength dependence and measurement geometry on the
radiance ratios. Conditions are limited to high reflectance
The degradation of the OMI instrument downstream of the diffusers is approximated by the change observed in the backup measurements (see Table 5) because the expected degradation of that diffuser is so small. To assess how these non-diffuser changes affect the OMI Earth-view measurements requires an independent estimate of measured radiance change. The estimated changes, shown in Fig. 29, are assessed by removing common seasonal and other cyclic variations. No attempt has been made to remove any putative long-term geophysical changes from the radiances.
Instrument changes related to Earth-view measurements are summarized in
Fig. 30. Signal changes for the solar QVD
measurements, shown in the same plot, are significantly greater. Note that
in the UV region (
The derived Earth radiance changes are confirmed by observing measured
signals (Fig. 31) over Greenland and Antarctica.
Assuming that the mean reflectivity of the ice surfaces has not changed over
the OMI mission, we conclude that the optics and detector have changed by
Spectral calibration trend over the mission for the radiance channel. Spectral calibration for the UV1 channel is strongly affected by the row-anomaly effect since 2009.
This conclusion is substantiated by the long-term trends seen in the OMI
radiances (Fig. 29). In this figure we show
de-trended and wavelength-, latitude-, time- and row-binned radiances. As an
example, for UV1 we select all the available data for image rows 6–10,
which are practically unaffected by RA at southern-hemisphere latitudes. We
show image row 2–7 UV2 trends for all latitudes and the radiances from the
low-reflectivity (< 10 %) subsample of the data. In addition, we
show the trend for the high-reflectivity (> 80 %) group for the
357–373 nm wavelength bin, keeping in mind that the onset of a major RA
event in January 2009 may have changed the OMI stray-light levels due to the
physical blocking of some Earth-viewing angles as well as additional
scattering of the Sun and Earth light. Hence, if the currently implemented
stray-light correction does not adequately capture the RA-related changes,
one should see different temporal behavior among the high- and
low-reflectivity sub-samples. The low-reflectivity scenery turns out to be
We directly examined the ratios of Sun-normalized radiances measured at
wavelengths separated by several nanometers to confirm that there is little
change in the spectral dependence of OMI's overall radiance calibration over
the course of the mission. The data shown in Fig. 32, for three of the OMI detector rows unaffected by the row anomaly, are
selected to minimize natural sources of trend and variability in the ratios
of radiances. The main geophysical effects which introduce time-varying
spectral dependence in back-scattered Earth radiances are Rayleigh and
aerosol scattering, trace-gas absorption, and Raman scattering. Because
these effects are much larger than the changes in the instrument spectral
dependence, and they are highly variable over space and time, particularly
over shorter scales, it is useful to isolate certain data so the impact of
these effects on the radiances is reduced. A total of 354 nm radiances are unaffected
by trace-gas absorption, and while 340 and 380 nm radiances have minor
O
The results in Fig. 32 show the monthly means of the wavelength ratios of 340 to 354 nm on the UV-2 detector and 354 to 380 nm from the VIS detector, for three detector rows over the course of the OMI mission (useful 354 nm measurements are made on both the UV-2 and VIS detectors). The trends in these ratios are less than 0.5 % per decade.
Small seasonal and interannual variations remain in the radiance ratios despite our efforts to minimize the wavelength dependent geophysical effects on the variability of these data. These variations are most likely from remaining geophysical effects such as residual solar zenith angle dependence, variation in cloudiness, and possibly aerosol contamination caused by volcanic events. They are not thought to be related to detector performance. The somewhat greater amplitude of the variations seen for the VIS detector ratios can be explained by the fact that the leading spectrally dependent effects at these wavelengths increase with greater wavelength separation, and the wavelengths on VIS are separated by 26 nm, whereas those on UV-2 are separated by 14 nm. This analysis is limited to the UV-2 and VIS detectors because radiances measured by UV-1 are much more sensitive to ozone, and the ozone absorption cross section varies dramatically over just a few nanometers in that detector's spectral range.
Changes in the line centroids of prominent absorption blends in
the solar irradiances observed in UV1
The orbital changes of the line centroids
Solar signal changes observed in the three channels for the timeframe 2005–2015.
Level 2 retrievals which use differential optical absorption spectroscopy
or principal components analysis techniques to derive trace-gas
information from the high spectral frequency structure in Level 1
reflectance measurements can be sensitive to wavelength errors as small as
The changes of calibration parameters based on the fit results (the second
wavelength calibration method) are shown in Fig. 33. Here we plot the first polynomial coefficient (
We complement the findings from Fig. 33 by
trending the wavelength registration provided via the first calibration
method, i.e., the preflight calibration adjusted by the OPB temperature
and, whenever applicable, the inhomogeneous slit illumination. As an
example, we take the daily OMI irradiance measurements, and for each row we
select prominent spectral lines spanning the sensitivity ranges of the OMI
spectral channels. For each row in each channel we calculate centroids of
these prominent absorptions. For a given line, in all rows the calculated
centroids show similar, to within sensitivity limits, time dependencies.
Hence, we average all the UV2 and VIS rows, however, limiting the averages to
the UV1 image rows 1–13, thus avoiding the FOVs experiencing anomalous
degradation rates (see Fig. 27). We additionally
average values over 3 consecutive months and subtract the early-mission
estimates from the line-centroid measurements.
Figure 34 shows changes in the line centroids for
the selected representative lines. Over the mission time, line positions
gradually shift at <
The long-term (mission time) and short-term (orbital) stability of the
instrument spectral response function is deemed important for reliable,
unbiased retrievals of the atmospheric trace-gas properties. Changes in the
instrument spectral response affect depths and widths of the detected
spectral features. In Fig. 35 we show variations
of the line-profile parameters derived from radiances for the line blend
around
OMI performance over the mission time, year 2005–2015.
Many trace-gas retrieval algorithms rely on solar reference spectra, thus creating an additional dilemma: should the referencing use static (usually, chosen at the beginning of the mission) or dynamic solar data? Choosing between two approaches, one should take into consideration a multitude of conflicting requirements. Among them is the possible different degradation rates in the optical channels acquiring radiance and irradiance data. OMI shows such differences, though they are relatively small. Also, one has to consider the gradual SNR decrease in the solar data (cf. Fig. 18). Even in the moderate-resolution OMI irradiances, the daily, monthly and long-term solar variability is prominent in the lambda < 450 nm domain, frequently exceeding 0.5 % in the strong spectral blends (Marchenko and DeLand, 2014), calling for a thorough evaluation of sensitivity of the L2 science products to the variable solar spectrum. On the other hand, any substantial (far exceeding the sensitivity of a typical trace-gas retrieval algorithm) long-term wavelength drifts may require extensive interpolations of the static solar data, thus augmenting the under-sampling biases (Kurosu et al., 2004).
The frequently used in the OMI L2 applications static solar spectrum was produced (T. Kelly, personal communication, 2017) from seven subsequent daily solar observations acquired between 28 December 2004 and 3 January 2005. This static reference spectrum is derived as an unweighted average of the daily observations, neglecting exceedingly large deviations from the corresponding row (i.e., FOV) and wavelength-dependent median values.
Analyzing long-term trends in the OMI L1B products, as well as values of calibration parameters, we conclude that, apart from the ongoing row anomaly, the instrument continues to perform well. Though still gradually unraveling, the row anomaly remains relatively stable since the latest incident in the summer–fall 2011.
One of the most noticeable trends is the 7-fold dark-current increase.
The RTS warnings, which are closely related to the dark-current readings,
have increased to 0.7 % of the CCD pixels used for data acquisition, or
to 5.6 % if one considers the binning factors (8 CCD pixels
The gradual decrease in the irradiance values can be primarily attributed to
degradation in the solar diffusers. The daily measured irradiances from the
QVD diffuser decreased by 6 % in the UV1 channel. The output from the Al
diffuser, which is used once per week, diminished by 3 % in the same
wavelength range. The rarely (once per month) used backup Al diffuser has
degraded by 2.5 % in the UV1 channel. Since the exposure times for the
weekly and monthly calibration cycles differ by 4 times, it can be safely
assumed that the registered 2.5 % degradation of the backup Al diffuser
is attributable to the complete optical pathway of the OMI irradiance
measurements (Fig. 2). We also register the
substantially (
In the RA-free areas the trends in the OMI radiances point to surprisingly
small changes, with good consistency among the UV1, UV2 and VIS channels:
the UV region shows a
The long-term wavelength drifts in the UV2 and VIS channels do not exceed 0.005 nm, attesting to excellent thermal and mechanical stability of the instrument. Gradual drifts in the UV1 range amount to 0.015 nm, with some evidence of wavelength dependence.
We perceive the row anomaly as the most formidable instrument problem that
renders unusable a significant proportion of the RA-affected rows (FOVs).
The anomaly was unequivocally detected in two rows in June 2007. Alternative
approaches point to the possibility of an even earlier incursion around the fall
2005–winter 2006. In May 2008 a large new group of rows became affected.
The row anomaly continued to develop since then, with the particularly swift
changes around January 2009 and the early fall of 2011. It has been relatively
stable since then. The latest small increase in the affected rows dates to
August 2014. Overall, the numbers of the RA-affected rows depend on the OMI
channel, with radically different latitudinal and seasonal behavior in the
UV1 and UV2 channels and comparable patterns in the UV2 and VIS ranges.
Considering the complexity of the temporal and spatial changes, in the summary
Table 6 we provide only indicative estimates of the
RA-affected rows. For example, currently about 33 % of the UV2 rows are
affected in the southern-equatorial parts of the OMI orbit. This increases
to
As appears from the presented data, OMI ages very gracefully, showing remarkably low radiance degradation and high wavelength stability. The most serious concern is the developing row anomaly. However, its spread has stabilized since the last rapid development in the fall of 2011. Assuming status quo, one may expect for the instrument to deliver useful science data for 5–10 additional years.
All analysis results presented in this article are based on the OMI Level 1B data. This dataset is publicly available at NASA's Goddard Earth Sciences Data and Information Services Center (GES-DISC, 2004).
This appendix describes how the wavelength registration of OMI was performed during the on-ground calibration period and how it is executed in flight. During the on-ground calibration period the wavelength calibration was performed using a PtCrNeAr spectral line source. In the analysis of the calibration data, small wavelength windows were used that contained exactly one spectral line, whose wavelength is accurately known. Five windows were used In the UV1 channel, and nine windows in the UV2 and VIS channels. In such a window the spectral calibration was performed by fitting the measured spectrum to a Gaussian function in the UV1 channel. In the UV2 and VIS channels a sum of a Gaussian and a function with a flatter top was used:
The fits were performed in pixel space. In this way for all windows the peak position of the spectral line in pixel space was determined. The peak positions together with their wavelengths are fitted to a fourth-order polynomial to obtain the wavelength scale. This wavelength scale is used to calculate the wavelength of a given column number in the L1B processor.
During the mission the wavelength assignment is done using two methods. The wavelength coefficients are obtained for both the radiance and irradiance measurements. In the first method the wavelength assignment is based on pre-launch and early in-orbit wavelength calibration parameters. These parameters are modified as a function of optical bench temperature:
For the second method, the wavelength calibration is performed by fitting an
accurately known solar spectrum, an ozone absorption spectrum and a Ring
spectrum to the measured spectrum. The reference spectrum is divided in 8
windows for the UV1 channel, 18 windows for the UV2 channel and 22 windows
for the VIS channel. These windows contain characteristic features of the
solar spectrum like Fraunhofer lines. For each window a fit of the measured
spectrum with the reference spectrum is performed in wavelength space. The
boundaries of a window are given by
and
The fit function is
The precision
where
The authors declare that they have no conflict of interest.
The authors would like to acknowledge the work of the large team of colleagues at KNMI, FMI, NASA and in industry that have contributed to the success of the OMI instrument. This work could not have been done without funding from the Netherlands Space Organization and NASA. Edited by: V. Sofieva Reviewed by: M. Dobber and one anonymous referee