1. Introduction
To validate model predictions of future changes to the earth’s climate, it is important to maintain measurements of the earth radiation budget (ERB) from space. ERB parameters are the emitted thermal or longwave (LW; 5 μm < λ < 100 μm) and scattered solar or shortwave (SW; 0.2 μm < λ < 5 μm) radiative fluxes leaving Earth. Such measurements, when combined with knowledge of the solar constant, tell of the net heat engine energy input that drives all weather and climate on the earth. The measurement accuracy and calibration stability required to detect model-predicted effects of cloud–climate feedbacks on the ERB has recently been estimated by Ohring et al. (2005). The standards called for are an absolute accuracy of 1 W m−2, a calibration stability of ±0.3% decade−1 for SW flux, and ±0.5% decade−1 for LW flux. The Clouds and the Earth’s Radiant Energy System (CERES; Wielicki et al. 1996) is currently the only satellite program monitoring global ERB parameters from space. For the CERES edition 2 (Ed2) data release, design specifications called for an absolute accuracy of ±1% and calibration stability of also around ±1% during an estimated 5-yr mission life (i.e., ±2% decade−1; see Wielicki et al. 1996). The new requirements for ERB climate calibration stability are therefore significantly beyond those originally specified for the CERES program. The target accuracies and stabilities are made all the more challenging given the discovery of contaminant spectral darkening (Matthews et al. 2005b), which significantly degrades CERES telescope transmission in the UV region. This paper details methods of estimating the stability of existing edition 2 SW CERES measurements, as well as those that have been adjusted to account for UV optical degradation using the “Rev1” spectral darkening factors (see NASA 2008a,b). Also, a new experimental calibration methodology as described in detail by Matthews et al. (2006, 2007a,b) is presented. These are efforts to assign coloration to the spectral darkening effects on the CERES optics while achieving a higher stability for ERB measurements. The results when this calibration is used to invert CERES data in a test edition are shown in validation studies as well as in comparison to edition 2 results. Finally, estimates of the potential stability of the new calibration when combined with regular raster-scan lunar data are made. This does not currently represent calibration intended for use in an official CERES data release. It is merely a summary of the work to date on compensating for contaminant issues on the CERES optics.
a. CERES mission and instruments
Three radiometric telescope channels are used by each CERES instrument to measure the ERB (Fig. 1a), each with a thermistor bolometer at its focus. Scattered solar flux is measured by the SW channel, which uses a fused silica filter to select Earth radiance between 0.2 and 5 μm. Emitted thermal flux is measured using the total channel. With no filtering optics, the “total” telescope is sensitive to all radiance in the range of 0.2 μm < λ < 200 μm. Daylight measurements of LW flux hence require subtraction of the SW channel signal from that of the total telescope in order to give the broadband-emitted thermal energy. A third window (WN) channel that uses a zinc sulfide/cadmium telluride filter allows CERES to measure narrowband thermal radiance in the range of 8–12 μm. Figure 2 shows example spectral responses of the three CERES channels as well as typical thermal and scattered solar Earth radiance. To date, five CERES instruments have been launched into orbit. The first, named ProtoFlight Model (PFM), was launched on board the Tropical Rainfall Measuring Mission (TRMM) in November 1997. PFM operated from January to August 1998 (8 months), when it was deactivated because of an instrument power regulator malfunction. The second and third CERES instruments were called flight models 1 and 2 (FM1 and FM2). These were launched on board the Earth Observing System (EOS) platform Terra in December 1999. FM1 and FM2 have been operational from March 2000 up to the current day (the power regulator fault that caused the premature failure of PFM was corrected in all later CERES instruments). PFM was reactivated for one month in March 2000 to allow comparisons with Terra. CERES flight models 3 and 4 (FM3 and FM4) were launched on board the EOS Aqua platform in May 2002. FM3 has been operational since July 2002 but the SW channel on FM4 malfunctioned in March 2005. This removed the ability to directly retrieve daytime ERB parameter measurements from that instrument.
The release of edition 2 CERES data occurred in six-month segments (Spence et al. 2004). Here, calibration parameters were updated based on regular views of onboard blackbodies for the total and WN channels. Changes to the detector signal when observing an onboard tungsten shortwave internal calibration source (SWICS) lamp (see Fig. 1b) were used to update gains for the SW channels. Such in-flight calibrations and a three-channel balancing technique described by Spence et al. (2004) were intended to provide the specified stability to the edition 2 CERES SW and LW flux measurements.
2. CERES spectral darkening and Rev1 adjustment factors
CERES edition 2 data have been released in the forms of Earth Radiation Budget Experiment (ERBE)-like and single scanner footprint (SSF) datasets. ERBE-like data use the same inversion methods of the ERBE mission (Barkstrom 1984), relying on the scene identification by the maximum likelihood estimation technique (MLE; Wielicki and Green 1989). SSF data use imager measurements taken from the same satellite to perform scene identification. PFM uses Visible and Infrared Radiometer System (VIRS) imager data (Simpson et al. 1996), whereas FM1–FM4 utilize measurements from the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments (Salomonson et al. 1989). With the production of several years of SSF edition 2 data from the Terra satellite, it became apparent that the measurements suggested a significant drop in the solar radiance scattered from the earth’s oceans. The magnitude of this was almost 2% within a period of less than 4 yr (see Fig. 3a). As described by Loeb (2004), this was not consistent with datasets from other solar wavelength Earth viewing instruments in orbit. Hence, attention was turned to possible causes of SW instrument degradation that would not show up using the edition 2 calibration methodology of Spence et al. (2004). A reasonable explanation seemed to be that the CERES optics were undergoing a significant drop in transmission of blue/UV photons because of optical contamination. However, little to no change in the visible to near-infrared (NIR) response would need to be occurring. This is exactly what occurred on the Long Duration Exposure Facility experiment (LDEF; Clark and Dibattista 1978), which retrieved an ERB radiometer after almost 6 yr in low Earth orbit (LEO) using the shuttle. Such an effect, described as “spectral darkening” (Matthews et al. 2005b), would not be detectable using the onboard SWICS calibration lamps because they are largely devoid of UV output (see Fig. 3b).
Proximity of two CERES units on both Terra and Aqua platforms (Fig. 1c) enabled the use of direct comparisons between nadir measurements made by the separate instruments. Comparing near-simultaneous nadir footprints sampled within 1.65 s of each other allows the monitoring of how one CERES instrument’s response changes relative to another on the same satellite. Until 2005, the CERES instruments spent the majority of the time operating in one of two orientations called cross-track (XTRACK) and rotating azimuth plane (RAPS) modes. The scan plane for XTRACK was held perpendicular to the satellite motion, which gave the ideal coverage for collecting ERB data. In RAPS mode, the telescope was continuously rotated in azimuth for purposes of measuring targets with multiple viewing/solar geometries. RAPS mode was necessary for the construction of sophisticated angular dependency models (ADMs; Green and Hinton 1996; Loeb et al. 2005), which are required to convert CERES measurements of radiance to flux (or irradiance).


Figure 3c shows Terra direct comparison of ERBE-like SW channel nadir footprint filtered radiance RFsw for the first five years of the mission [i.e., this is the percent difference in filtered radiance between FM2 and FM1 defined by Eq. (2)]. It clearly indicates how the instrument operating in RAPS mode always drops in SW response compared to its XTRACK mode counterpart. Until 2002, the instruments alternated every three months between RAPS and XTRACK modes (creating the oscillatory nature in Fig. 3c at the mission start). From then until mid-2005, FM2 was held continuously in RAPS mode, which resulted in a steady drop in its SW response compared to FM1. Figure 3c shows both the direct comparison of all-sky and clear-ocean footprints separately. The 2002–05 period tells how the relative drop in the RAPS instrument SW response to the “blue” scene of clear ocean is significantly greater than for all sky. Figure 3c also therefore suggests that the RAPS instrument drop in optical throughput for an Earth scene with high fractional blue/UV content is more severe than for the all-sky case (as observed by LDEF in Fig. 3b).
Interestingly, the SWICS calibrations indicated no significant changes in SW detector radiometric gains for FM1 and FM2 during this period (see Spence et al. 2004). With no apparent change in gain, the 2% drop in Earth scattered flux within 4 yr (Fig. 3a) could only be caused by a significant but undetectable reduction in optical transmission and hence filtering factor fi [Eq. (3)].
With this drop in optical response being so significant to affect climate records, it was decided to develop adjustments or “revisions” to edition 2 SW data that would compensate for spectral darkening effects. These adjustments were derived based on two fundamental assumptions. First, it was presumed that the SWICS lamp output is perfectly stable in flight and in a spectral region unaffected by LDEF-like degradation (Fig. 3b). Second, it was assumed that the optical degradation only occurs when an instrument operates in the RAPS mode. This allows the XTRACK instrument to be used as a calibration standard from which the drop in filtering factor fi of the other instrument can be estimated [for full derivation of the Rev1 factors, see Matthews et al. (2005b)]. Because, as shown in Fig. 3c, there was a significant difference in the changes in response to the scenes of all sky and clear ocean, it was decided to derive two different revisions for each instrument that cover both of these scenes separately (i.e., the all-sky adjustment is multiplied with unfiltered Ed2 SW for all scenes except clear ocean). Such adjustments for the Terra instruments are shown in Fig. 3d. They suggest a drop in FM1 response of just over 1%, whereas the FM2 instrument, with its longer time in RAPS mode, degraded by 1.5%–2% over the same period. As expected, Fig. 3d illustrates how the estimated darkening occurs in 3-month periods and ceases completely for FM1 beyond 2001 (when that instrument was placed permanently in XTRACK, thus preventing any suspected darkening). Comparison of the Rev1 values for all sky and clear ocean again shows how the darkening of response occurs to a greater extent for clear ocean (as the ocean scene has a higher proportion of spectral energy situated toward the blue/UV end of the spectrum). Such monthly revisions were designed for direct application to already released edition 2 CERES unfiltered SW data products and are available from the CERES data quality summaries (see NASA 2008a,b; Fig. 3e). Once adjusted by using these figures, the CERES SW data are then called edition 2 Rev1.
3. Estimates of CERES Ed2 and Ed2 Rev1 SW data stability
The work of Loeb et al. (2007) performed multi-instrument comparisons of CERES top-of-atmosphere SW radiance with other Earth observing instruments on both the same and different satellites. These showed that there was good agreement between Rev1-adjusted tropical ocean Terra SW data and anticorrelated measurements of the photosynthetically active radiance (PAR) product made by the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) ocean color instrument (Hooker et al. 1992). This was significant because the SeaWiFS instrument uses monthly views of the Moon to update the gains of its photodiode detectors, giving its radiance measurements very good stability. The FM1 Ed2 Rev1 SW flux measurements were also found to agree with the collocated MODIS solar radiances to within ±1% decade−1. Rev1-adjusted CERES tropical SW measurements were also compared between the Aqua and Terra CERES instruments (FM4 and FM1). Here, however, the Aqua measurements were found to drop in comparison to those made on Terra with 95% confidence in the difference between relative trends. This indicated that the use of the Rev1 assumptions had not provided stable calibration of either Terra or Aqua SW (or perhaps both). One possibility is the suspected ground contamination of the Aqua CERES optics discussed in Matthews et al. (2007b). This may have resulted in a slightly different contaminant affecting the Aqua telescopes, one that continues to degrade in throughput whether operating in RAPS or XTRACK mode. Another possibility is highlighted by the apparent negligible change in Terra SW gains indicated by the SWICS calibrations (Spence et al. 2004). In all cases with the CERES total channels, the radiometric gain of the CERES bolometers was seen to increase in the vacuum of space by 0.5%–1%, based on regular views of the onboard blackbodies. Physically, this is as expected because the bolometers operate in a Wheatstone bridge configuration, relying on the temperature difference induced in the irradiated active flake when compared with a shielded compensating flake. Outgassing from the bolometer in a vacuum will therefore serve to reduce the thermal mass of the detector and give a greater temperature change per unit of radiance absorbed. As described in Matthews et al. (2005a), this will increase the effective first-time constant gain of the bolometer and thus increase gsw in Eq. (2). It was therefore unexpected that the Terra SW channels should exhibit no gain increase throughout the mission, implying perhaps that the onboard lamps had actually dimmed in the first 4 yr.
The Terra/Aqua trend discrepancy alone highlighted that an independent SW stability metric was needed in order to be sure of which physical spectral darkening effects were afflicting each CERES instrument. The metric chosen was that of deep convective cloud (DCC) albedo. DCC is defined as tropical ocean-region clouds with optical thickness τ > 120, temperature < 205 K, and a MODIS 0.6-μm radiance uniformity within the CERES footprint of less than 3% (where the footprints were found using the cloud properties stored in the SSF product). As very optically thick, cold, and uniform clouds, these are assumed to represent ice particle reflectors on the edge of space [because, as in Kratz et al. (2002), they are presumed to have very little water vapor or ozone above them]. Described in Matthews et al. (2006), the radiance measurements from these clouds are adjusted by using the state-of-the-art anisotropic factors (Loeb et al. 2005) into outgoing irradiance. This is then adjusted to overhead Sun using TRMM direction models (N. Loeb 2005, personal communication) and combined with the incoming solar flux from that day to give a DCC albedo figure. It is noted that this metric will therefore have a slight dependence on the stability of cloud retrievals from the MODIS and VIRS instruments (Minnis et al. 1998).

This DCC metric then gives a new way to estimate stability of edition 2 products. Figure 4a clearly shows an overall drop in all Terra/Aqua SW data that correlates with time spent in RAPS mode. Figure 4b then shows the same edition 2 data after the Rev1 adjustments have been made; note that there are no Rev1 adjustments for PFM. Assuming that the DCC albedo is indeed a stable metric, this enables analysis of the quality of the Rev1 adjustment for restoring climate stability to CERES data. As described in section 2, the Rev1 adjustment was derived using the assumption that the onboard SWICS lamps were perfectly stable and that instrument optics degrade only while operating in RAPS mode. The adjustment appears to have successfully reduced the difference between the FM1 and FM2 measurements of DCC. However, both FM1 and FM2 (Terra) now exhibit statistically significant positive trends in Fig. 4b, implying that the Rev1 adjustment had overcompensated for the optical degradation (see Table 1). As mentioned, a possible physical cause of these ∼+1% decade−1 trends is that the Terra SWICS lamps dimmed during the mission. This resulted in no SW gain changes being made in the edition 2 release. Therefore, the asymptotic rise of the FM1 and FM2 curves (Fig. 4b) may somewhat represent the true gain change of the Terra SW bolometers as they outgas (note the resemblance with the observed total channel gain increases using blackbodies displayed in Fig. 8). Conversely, the Aqua instruments FM3 and FM4 continue to show significant, although reduced, negative trends after the Rev1 adjustment (the FM4 trend is now just outside statistical significance because of lack of data). This is consistent with Loeb et al. (2007), who found a significant +3.8 W m−2 decade−1 (+1.5% decade−1) trend when FM1 SW data were compared to FM4 globally. Again from the Rev1 assumptions, the only physical cause of a continued drop in Aqua DCC albedo is that the contaminant continued to polymerize and darken, even when the instrument was operating in XTRACK mode. This suggests that the Aqua contaminant may differ somewhat from that afflicting the Terra instruments [possibly a result of the suspected ground contamination of the Aqua instruments discussed in Matthews et al. (2007b)]. However, the excellent agreement in Loeb et al. (2007) between the Rev1-adjusted FM1 SW tropical ocean data and the anticorrelated SeaWiFS PAR must be considered. It is likely that the tropical ocean scene spectrum typically has a higher proportion of its energy in the UV region than DCC. This could mean that although Rev1 appears to overcompensate by about 0.5% for the overcast DCC scene, it may in fact be a suitable compensation for the change in optical response to tropical ocean SW radiance.
Also strikingly apparent in Fig. 4b is an apparent 1% drop in SW measurements with each new satellite mission between TRMM (PFM) and Terra (FM1 and FM2), then Terra and Aqua (FM3 and FM4). Assuming that no significant biases were introduced because of the differences between TRMM, Terra, and Aqua ADMs, a possible physical cause of this is a degradation of the mirrors contained in the Transfer Active Cavity Radiometer (TACR). This was used to determine SW calibration source output during the ground calibration of the CERES instruments. Because the TACR gain is determined in the LW by using a blackbody, a 1% degradation in the SW reflectivity of its mirror will translate directly to a 1% overestimation of the CERES SW gain [i.e., gsw in Eq. (4)]. At present, this cannot be verified because the TACR is still in use in calibration of future CERES units; it does, however, warrant further investigation.
In summary, the use of DCC albedo to investigate stability of existing CERES calibration suggests that all edition 2 SW data exhibit significant negative calibration drifts, most likely because of the RAPS degradation. The Rev1 adjustments severely lessen these trends in Aqua data although they are not removed beyond statistical significance. For Terra, the Rev1 adjustments seem to have overcompensated, inducing slight positive trends in SW measurements of DCC. Although not the direct subject of this paper, the absolute SW accuracy differences between the three satellite platforms are also highlighted, with Terra 1% below TRMM and Aqua a further 1% below Terra.
4. CERES spectral darkening calibration
Section 3 showed that the Rev1 adjustments appear to have restored CERES SW measurements to the specified ±2% decade−1 stability (i.e., ±1% per 5-yr lifetime stability). This, however, is not sufficient to meet the requirements of Ohring et al. (2005), meaning that a more rigorous calibration methodology is required. The following section summarizes the work of Matthews et al. (2006, 2007a,b), who attempt to spectrally resolve the contaminant effects on CERES calibration.
It was decided to utilize imager data contained within the SSF product to give detailed information on the scenes viewed by the CERES instruments. This would allow a MODTRAN spectral signature to be assigned to each footprint. That information was tied to the raw detector output or filtered radiance RF [Eq. (2)]. Hence, both the effects of bolometer gain change and optical degradation were left present and undisturbed in the CERES data. The next step was to develop a comprehensive model of how contaminant could mobilize to the optics and then polymerize. The assumption is made that the contaminant arrives on the optics only if the instrument is in RAPS mode, when the telescope is exposed to the ram direction of travel (Figs. 5a,b). Then, LEO atomic oxygen enters the telescope and is free to interact with optical coatings or some contaminant reservoir. Molecules can then be mobilized to other optical surfaces and then fixed to them by Earth scattered UV.
With knowledge of contaminant arrival rate N(t), which acts as a forcing function to Eq. (10), it is possible to use a Z domain–derived recursive filter (see, e.g., Matthews et al. 2005a) and simulate the thickness of polymerized contaminant B(t) on the SW optics for each month of the mission. Such simulations for the CERES instruments are shown in Fig. 7. These illustrate how, after the FM1 instrument was locked in cross-track mode from the end of 2001 onward, arrival of contaminant ceased. Hence, the thickness B(t) then approaches an asymptote as the remaining type A molecules continue to polymerize into the type B absorbers. However, on the FM2 instrument, the thickness of molecule B absorbers continues to grow because of prolonged exposure to ram direction (Fig. 7b, right). Eventually, a fall off occurs toward the end of the period as a result of the contaminant reservoir becoming depleted, reducing the monthly arrival rate N(t) (Fig. 7b, left; as mentioned this may also be due to a drop in the atomic oxygen flux).








With the estimates obtained of changes to SW gains and spectral responses, the next step is to use biweekly blackbody calibration data to estimate the changes to the total and WN channel gains. Then the direct compare balancing perturbation described in Matthews et al. (2007b) is applied. This makes very minor adjustments to the gains so that two instruments on the same satellite measure identical nighttime LW and WN radiance. The adjustment also ensures that all instruments measure the same DCC albedo as the PFM instrument (believed to be the most accurate in the SW as it was first calibrated when the TACR mirrors were fresh). The derived gain changes for all five CERES instruments are shown in Fig. 8. These illustrate how typically the gain of the total or SW channel increases by 0.5%–1% over the course of a mission (because of bolometer outgassing, etc.). The blackbody calibrations for the FM2 instrument suggest a seasonal cycle in the total channel gain that correlates with the changes in orbital beta angle and hence the solar heating of the instrument. For this reason, the direct compare balancing of Matthews et al. (2007b) utilized the FM1 total channel calibrations to define this seasonal cycle (through the use of nighttime LW direct compare). Hence, it remains in the test edition total channel gain shown in Fig. 8c, because it is believed to be a real variation in the gain
Interestingly, the WN channel gain is often seen to decrease based on blackbody calibrations. It is highly likely that this is not actually because of a decrease in the bolometer gain. Instead there may be a drop in the throughput of the WN filter as a result of the same contamination that afflicts the SW channel when in RAPS mode (note that the WN filter is in the same place in the telescope as the SW filter, as shown in Fig. 5b).


This is also done for the clear-water and clear-land scenes, although for these the presence of significant water vapor means that the WN channel cannot be relied upon to give an accurate measure of that thermal signal in the total channel. Hence, the estimates of clear-water and clear-land scattered TSRClr.W(k) and TSRClr.L(k), respectively, are only used to detect relative drifts rather than the absolute response [i.e., in the first month, TSRClr.W(0) and TSRClr.L(0) are forced to equal the accurately derived TSRdcc(0) value, assuming the ground measurements of the total channel UV response shape are accurate, as in Matthews et al. (2007a)].
Figures 9a–d illustrate both Terra and Aqua test edition estimates of the changes in TSR for the scenes of DCC, clear water, and clear land. In all cases, the results suggest that the total channels are less responsive to SW radiance at the mission start than the ground measurements imply, by greater than 1% [i.e., TSRi(0) < 0.99]. In fact, the size of the required start-of-mission drop in response increases with each new instrument. The more recent FM3 and FM4 instruments appear to have a 3% less responsive total channel for solar wavelengths than ground calibration suggested. Again, this may be because of a continued degradation of the SW response of mirrors used in the TACR for the ground calibration. Interestingly, all five instruments show a significant mission life dispersion in their changes in response to DCC, clear water, and clear land. Figure 9b shows that, in the case of FM2, a >1% increase in DCC response is accompanied by a 2.5% decrease in transmission of clear-water scattered sunlight (which has a higher UV percent content). A physical explanation for this could be that the total channel mirrors are subject to different types of contaminant that affect separate spectral regions. The first may be similar to that afflicting the SW channel, absorbing strongly in the UV and polymerizing with continued exposure to Earth scattered sunlight. A second contaminant is assumed to be more like a black absorber, acting like soot on an optic and reducing its net throughput. It is then possible that exposure to atomic oxygen in the RAPS mode serves to clean this second contaminant from the mirror, increasing the net telescope throughput (like atomic oxygen cleaning as found on LDEF). Finally, it has to be assumed that there is a third contaminant or mirror degradation mechanism that affects only the NIR response (1.5 μm < λ < 2.5 μm). This is because, as shown in Figs. 9a–d, the total channel response to the “red” scene of clear land is very close to or even below that of the “white” DCC scene. This implies a reduced blue and red scene response compared to that for the white DCC target. The only explanation is for degradation to be occurring in both the UV and NIR spectral regions and to a greater extent than for the visible region.
Figure 10 then compares the resulting test edition–estimated UV/visible changes to all CERES total channels (Fig. 10, right) with those found for the SW (Fig. 10, left). These indicate how in all cases the total channel optics darken considerably in the UV, indeed to a greater extent than was found to occur in the SW channels. At the same time, all total channel telescopes also show a net increase in throughput for most visible radiance of wavelength greater than 0.5 μm. This again is a curious observation, the precise cause of which is also not yet known. The assumption was of the presence of multiple types of contaminant. Some are polymerizing and/or with strong NIR absorption lines. Another is perhaps a sootlike black substance that is cleaned from the optics throughout the mission by atomic oxygen. These assumptions may be valid; however, further investigation is warranted.
5. Validation of test results and comparison with edition 2
To test the success of the spectral darkening calibration parameters, an offline run of a test edition was made at the National Aeronautics and Space Administration (NASA) Langley Research Center by using the gains and spectral responses presented in this study. The most fundamental check on the SW calibration stability comes from observing the resulting DCC albedo after CERES data have gone through the full SSF inversion process. The test edition DCC albedo is displayed in Fig. 4c and shows that all CERES instruments have been successfully placed on the PFM (TRMM) SW radiometric scale. Also, as shown in Table 1, none of the instruments now measures trends in the DCC stability metric to statistical significance.
A second and more involved check on the calibration is to observe the direct comparison between near-simultaneous nadir unfiltered footprints
Figures 11a and 12a show significant mission life trends in edition 2 direct comparisons, especially for the clear-water scene. Also note in Fig. 11a the significant and increasing Terra scene dispersion between the blue clear-water and red desert scenes. In the Rev1-adjusted data (Figs. 11b, 12b), these trends are significantly reduced but the dispersion largely remains. Even though a separate Rev1 adjustment was derived for clear ocean, this was based on the ERBE-like scene identification, unlike the test data, which used the SSF imager radiances to identify clear water. The ERBE-like scene of clear ocean is found by MLE and hence is likely to contain more cloud contamination than the SSF scene clear water. Therefore, it has less UV percent content, possibly making the Rev1 adjustment insufficient for application to the SSF clear-water scene. In the test edition for Terra shown in Fig. 11c, all the trends and red/blue scene dispersion are decreased significantly [as the result of minimizing the quantity ϒ in Eq. (14)]. A slight trend is still present in clear water. This is most likely because of the slight difference in the model inversion using Eq. (4) and that of production as described by Loeb et al. (2001); also, clear water is a very “dark” scene, so a ∼+0.2% drift is very small in terms of watts per meters squared.
Note the 1% start-of-mission scene dispersion for Ed2 Aqua SW direct compare between red desert and blue clear water (see Figs. 12a,b). As mentioned earlier, it is suspected that the Aqua CERES optics were contaminated on ground before launch. Therefore, it may be possible that this scene dispersion at the mission start is because the SW spectral response shape of one or both of the Aqua instruments did not precisely match that measured in ground calibration. Hence, it is assumed that one of the instruments (in this case, FM4) had a nonzero thickness of contaminant at the mission start. This thickness is iteratively determined before the final balancing of SW gains is performed (for full details, see Matthews et al. 2007b). Figure 12c then shows the results of Aqua SW direct compare using the test edition run. This indicates that the 1% initial scene dispersion is removed and the slight trends in Ed2 and Ed2 Rev1 are significantly reduced.
Figure 13 shows Ed2 and test edition direct compare for both night and day unfiltered LW measurements on Terra. As indicated earlier, dispersion in direct compare suggests inaccuracies in the precise knowledge of telescope spectral-response shape (because the CERES bolometers are very linear detectors). Interestingly, Fig. 13a shows a 0.5% dispersion between the warmest and coldest nighttime scenes (i.e., clear water and overcast). This suggests slight inaccuracies in one or both of the Terra total channel spectral responses in the 5–10-μm range (see Fig. 2). Because the new calibration methodology makes no attempt to alter the spectral response in this wavelength region, this dispersion remains in the nighttime direct compare for the test edition (Fig. 13b). However, the nighttime balancing of Matthews et al. (2007b) has removed the near −0.5% trend in the edition 2 plot as well as the seasonal cycle present in the overcast direct compare (see Fig. 13a). Because stability of nighttime LW currently relies entirely on blackbody calibration, it is thought that this drift was caused by anomalous variation in the FM2 blackbody output. This is because the FM2 total blackbody calibrations showed a variation that correlates to the initial 15-min orbit shift of Terra from 2000 to 2002. This may mean that the FM2 blackbody temperature control may be affected by the change in solar heating as the orientation of the instrument and the Sun varied during the orbit shift [hence, why in the Terra balancing of Matthews et al. (2007b) FM1 is used as the calibration standard].
It is true to say that the CERES measurement of daytime LW radiance is the most complex to perform. This is because it requires subtracting the SW channel signal from that of the total to measure only the intensity of thermal photons. Such complexities are highlighted by the 1.25% dispersion between hot and cold scenes shown in the edition 2 daytime LW direct compare of Fig. 13c. Throughout the mission, this plot also shows a −1% drift in the difference between FM2 and FM1, indicating significant calibration drifts in one or both of the instrument’s daytime LW measurements. With the initial scene dispersion greater than that seen at night (Fig. 13a), the only explanation is inaccurate knowledge of the solar wavelength spectral response shape of one or both of the total channels. Hence, as with the SW channel and described by Matthews et al. (2007b), it is assumed that one of the total telescopes (FM1) was contaminated before activation. The optimum start of mission contamination is then iteratively calculated based on direct compare data (as in Matthews et al. 2007b). The Ed2 three-channel balancing of the SW and total spectral responses (Spence et al. 2004) used gray changes to the solar wavelength region of the total channel (that is to say the entire spectral response below 3 μm was moved up or down by the same amount). Section 4 showed how the spectral darkening analysis suggests that the total channel optics undergo severe UV degradation even in comparison to the SW channel. It is therefore likely that the drifts seen in Fig. 13c occur because the Ed2 gray changes are not sufficient to account for the varying changes in response to solar radiance scattered from clear water and deserts. Figure 13d shows that the spectral balancing of Matthews et al. (2007a) and cross-instrument unification of Matthews et al. (2007b) have served to almost completely remove the daytime LW additional scene dispersion. Also the trends between the two units are significantly reduced.
Figure 14 shows the same direct comparison data for the LW measurements from the Aqua platform. Figures 14a,b show excellent agreement between the two instruments for nighttime direct compare in both the Ed2 and test edition run. This suggests that the knowledge of LW spectral-response shape and blackbody stability on Aqua may both be superior to that achieved on Terra.
Figure 14c shows a far more significant scene dispersion of 0.5% for the daytime LW Ed2 release, which grows and varies significantly throughout the mission. As with Terra, the spectral darkening studies found significant UV degradation of the Aqua total channel telescopes. Once this is accounted for in the test edition run (Fig. 14d), the increasing drift in this dispersion is significantly reduced. However, there remains a 0.5% dispersion and seasonal cycle between the red desert scene and the white overcast scene. As stated earlier, the Aqua optics are suspected to have received contamination on the ground. It is therefore possible that one or both of the total channels had developed absorption in the 1.5–2.5-μm region before launch. Unfortunately, the spectral darkening studies give no way to verify or characterize this; hence, the desert dispersion remains in the test edition.
Finally, Fig. 15 shows Ed2 and test edition direct comparisons of nighttime WN unfiltered radiance. Comparing Ed2 Figs. 15a,c with test edition Figs. 15b,d indicates the success of the all-sky nighttime gain balancing technique of Matthews et al. (2007b). This was designed to bring WN measurements by different instruments on the same satellite to a common radiometric scale. Also, it is of significance for the general theory behind this study to compare Figs. 15a,c with Figs. 11a and 12a, respectively. Note the similarity in shape between SW and WN direct compare on both Terra and Aqua platforms (e.g., with Terra being oscillatory in nature before a steady decline after FM2 was locked into RAPS mode). From Fig. 8, it was noted that the WN channel signal when viewing onboard blackbodies actually decreased in most cases. Because the effective responsivity of bolometers tends to increase because of outgassing in the vacuum of space, it was suggested that this might be caused by the RAPS contaminant-reducing telescope throughput in the WN spectral region (because the WN filter is in the same optical train position as the SW channel filter, as shown in Fig. 5b). Hence, the similar drop in Ed2 RAPS instrument WN response relative to its XTRACK counterpart further strengthens the contaminant mobilization theory on which the SW spectral darkening model was based. Note that the slight drops in WN gain indicated by blackbody data were deemed below the threshold of the noise within the calibrations (hence, why the minor RAPS degradation could not be completely removed in the Ed2 data release). Importantly, this also implies that the RAPS mode contaminant does have LW absorption properties. Unfortunately, there is no way to distinguish between gain and LW optical response changes based solely on blackbody calibrations. Hence, this work is forced to assume the LW transmission of the contaminant is spectrally flat. So, these gain adjustments hence account for both changes in bolometer responsivity and optical throughput at the same time. Providing the assumption of contaminant LW transmission uniformity is a fair approximation; however, the total channel calibration presented here should yield good daytime LW stability, beyond that of the Ed2 release.
Figures 16, 17, and 18 then show the percent differences of the test edition run with the already released edition 2 (and the user-adjusted SW Ed2 Rev1). In all cases, the nighttime LW and WN results in the test edition remain largely unchanged from edition 2 (because of a reexamination of the same blackbody data used for the Ed2 release). The large start of mission change to FM4 WN was to lower Aqua WN data to match the level suggested by the FM3 blackbody (see Fig. 18f). This was based on the suggestion by Matthews (2008) that analyzed CERES lunar data to show that the Aqua WN measurements were significantly above those of Terra. The Terra instruments are more trusted because, unlike those on Aqua, they are not suspected of ground contamination. Use of DCC albedo to place all SW measurements on the PFM radiometric scale results in significant increases in Terra and Aqua SW flux. However, throughout the mission, the Terra test edition SW tends to drop when compared to Ed2 Rev1 for all scenes except clear water (Figs. 17a,e). As mentioned, this is because the SW model and DCC albedo suggested that the SWICS lamps had dimmed on the Terra mission, resulting in the gain inversion value being incorrectly held constant. Conversely, the Aqua test edition SW shows significant positive trends when compared to edition 2 Rev1 (Figs. 18a,e). This is because, as the spectral darkening model found, the Aqua contaminant tended to have a far longer polymerization time constant than that of Terra. Hence, the Rev1 adjustment failed to adequately compensate for continued degradation of the Aqua instruments, even when operating in XTRACK. Interestingly, the PFM SW test edition tends to drop in comparison with Ed2 in the first 8 months. Then, in the month of March 2000, when PFM was temporarily reactivated, the scenes of overcast and desert remain below Ed2 levels. All-sky water and clear water, however, show an increase in the test edition. This is because PFM test edition calibration actually relies on the SWICS lamp to determine gain changes. The suggestion from the lamp is that the SW channel gain increased by over 1% (Fig. 8a). However, the PFM DCC albedo signal in Fig. 4a remains constant within statistical limits (note that no SW gain changes were made in the PFM Ed2 release becuase it was thought at the time that the lamp had become brighter). If the PFM SW gain gsw had increased by 1%, as suggested by the SWICS, the conclusion can then be drawn that the SW optics must have at the same time degraded by a similar amount. This resulted in no significant change to the product gswfdcc. Hence, for the test edition, the monthly contaminant thickness B(k) used in Eq. (12) was simply found by iteration. This was done by assuming that PFM was subjected to the same contaminant type as Terra and to keep DCC albedo constant as the gain is increased.
Figures 17c,g and 18c,g show that the Terra daytime LW has tended to increase in the test edition compared to Ed2. This is because of the spectral balancing of Matthews et al. (2007a) that required a lowering of the total channel solar response from the mission start (see Fig. 9). A lower total channel solar response will cause a lower SW signal being subtracted from that of the total in the inversion of Loeb et al. (2001). This therefore results in a higher daytime LW result. Terra test edition day LW starts off 0.5%–1% higher than that of Ed2 and depending on the scene tends to increase in time by as much as 1% throughout the mission. For Aqua, the greatest initial increase is in cold scenes such as overcast, and then this increase actually tends to diminish throughout the mission.
6. Test edition calibration stability estimates
Ohring et al. (2005) detailed the calibration stability necessary to detect model-predicted changes to the ERB resulting from cloud feedbacks. These are currently one of the largest uncertainties in predictions of future climate change. Anthropogenic loading of the atmosphere with greenhouse gases is expected to perturb the climate at a rate of about 0.6 W m−2 decade−1. Models estimate that cloud–climate feedback could then further modify this forcing by ±25%, or ±0.15 W m−2 decade−1. Cloud radiative forcing (CRF), the difference between clear and cloudy flux, is measured at around 50 W m−2 for SW and 30 W m−2 for LW. The model-estimated cloud feedback perturbation of ±0.15 W m−2 decade−1 therefore represents ±0.3% of the SW and ±0.5% of the LW CRF signal. Hence, to detect CRF trends with 95% confidence, CERES calibration stabilities of ±0.15% and ±0.25% decade−1 are required for SW and LW flux measurements, respectively (i.e., half of the 0.3% and 0.5% figures).







There is one CERES instrument–designated FM5 still set to launch soon on the National Polar-orbiting Operational Environmental Satellite System (NPOESS) Proprietary Project (NPP) platform. If this instrument begins raster scans of the Moon immediately, a prediction of the possible FM5 calibration stability can be made, as in Fig. 19d. Because here the term Δtnm = 0, the lunar data become useful far earlier in the mission, achieving the required night and day LW stability in less than 5 and 10 yr, respectively.
7. Conclusions
This paper summarized attempts to characterize the spectral changes occurring to all existing CERES instruments while in flight. The effects of spectral darkening of optics through contamination were shown to induce negative calibration drifts in all CERES Ed2 Terra and Aqua measurements of Earth scattered SW. However, the user-applied Rev1 adjustments were seen to restore Ed2 SW calibration stability to that specified in the CERES program (±2% decade−1). This was determined based on the stability metric of DCC albedo. Such results suggest that the Terra onboard lamps had dimmed somewhat and that the Aqua contaminant continued to polymerize and degrade the optics even when in the non-ram-exposed XTRACK mode. Unfortunately, this stability is not currently thought as sufficient to observe the model-predicted effects of cloud feedback forcing on the ERB. Therefore, a new CERES calibration methodology that attempts to include spectral coloration changes to the inversion/unfiltering process was presented. This again used the stability metric of DCC albedo combined with a comprehensive contaminant mobilization/polymerization model. The technique has provided physical explanations for most of the calibration changes occurring to the CERES instruments. Spectral darkening appears to be caused by optical exposure to the ram direction of travel, which results in contaminant arrival on the telescope and further polymerization by Earth scattered UV. However, some observations still remain somewhat unexplained, such as the apparent large rise in tota channel responsivity to DCC scattered solar accompanied by a significant drops in UV and NIR radiance response. Some possible reasons involving different types of contaminant on total channel mirrors were presented. However, further investigation may be needed to fully diagnose the causes of changes to total channel telescope transmission.
A sensitivity study was also performed to quantify the stability provided by use of this new calibration methodology. Table 2 shows estimates of the smallest climate signal that can be detected using this test edition calibration on CERES data up to and including December 2006 (with the smallest signal that could ever be detected given 15 yr of data also shown in parenthesis). These suggest that given sufficient length of the data record, the desired stability in SW calibration of ±0.3% decade−1 (2σ) is possible by using the methods presented here. It must again be noted that this SW calibration does assume a changing climate will not significantly alter deep convective processes. There is currently no evidence to suggest that a warmer/colder Earth would lead to an altered population density of clouds with optical thickness τ > 120. However, this will need verification by future Earth observing missions such as the Climate Absolute Radiance and Refractivity Observatory (CLARREO; available online at http://clarreo.larc.nasa.gov/index.html). Hence, for the moment, the SW stability figures presented represent the “best case” calibration possible using the methodology described.
The conclusion was also drawn that the onboard blackbodies cannot provide the LW stability necessary to detect cloud feedback perturbations to thermal climate forcing (hence, why the current LW stability in Table 2 is double that of the required ±0.5% decade−1 figure). However, it is suggested that if the spectral darkening calibration methods are combined with regular raster scans of the Moon, then the requested thermal calibration stability becomes a possibility. This, of course, is dependent on the satellite platform, the CERES instrument, and the MODIS imagers continuing to operate for periods beyond their predicted lifetime. At present, it is not known how realistic this requirement is. However, in the event of instrument failure and potential data gap, a further study based on the noise in both DCC and lunar data could be performed. This would then determine the detrimental effects of a break in climate data so that optimal use is made of all available CERES measurements. As indicated by Fig. 19d, providing FM5 begins regular raster scans of the Moon immediately after activation; then, within nine years, all of the Ohring et al. (2005) stability targets are met. Because, at the time of writing, FM1 and FM2 are merely 6 months from completing nine years of continuous operation, this may be a very achievable goal. It is also noted that the climate variable being measured (e.g., CRF) will contain its own autocorrelated noise, which will add further independent uncertainty to the figures in Table 2.
As for the absolute SW accuracy of test edition measurements, it is by no means straightforward to assess the impacts of potential ground contamination or TACR mirror solar response degradation. DCC albedo has been used here to place all CERES instruments on the PFM SW radiometric scale. This assumes that it is the most accurate, because that instrument was calibrated when the TACR mirrors were new. However, at this point, it is not suggested that the accuracy of test edition SW is beyond that originally specified for the CERES project (Wielicki et al. 1996). To quantify the absolute accuracy of LW, the 0.5% scene dispersion in night LW direct compare (Fig. 13b) will also need considering. This is accompanied by the discovery by Matthews (2008) that thermal measurements of the Moon by FM1 and FM3 can differ by >0.5%. Hence, future work separate from this study is needed to fully quantify CERES absolute accuracy and assess if it can meet those specified by Ohring et al. (2005). Further improvements in the accuracy of ERB measurements will rely on better ways of determining ground-to-flight shifts in broadband calibration [e.g., the solar calibration design proposed in Fig. 8 of Matthews (2008), which would also allow monitoring of any climate change–induced shifts to deep convection].
Finally, it is important to again note that the calibration methodology described in section 4 is not currently used in any official edition of CERES data. This is simply a summary of the spectral darkening calibration studies and an estimation of the stability they can provide. However, if deemed appropriate, then the methods presented here may aid in the production of a forthcoming release of CERES ERB data.
Acknowledgments
This work was supported by the NASA Science Mission Directorate and is dedicated to the memory of Tony Slingo. Many thanks to all those in the CERES instrument working group and science team for their advice, help, and patience.
REFERENCES
Barkstrom, B. R., 1984: The Earth Radiation Budget Experiment (ERBE). Bull. Amer. Meteor. Soc., 65 , 1170–1185.
Clark, L. G., and Dibattista J. D. , 1978: Space qualification of optical-instruments using NASA Long Duration Exposure Facility. Opt. Eng., 17 , 547–552.
Green, R. N., and Hinton P. O. , 1996: Estimation of angular distribution models from radiance pairs. J. Geophys. Res., 101 , (D12). 16951–16959.
Hooker, S. B., Esaias W. E. , Feldman G. C. , Gregg W. W. , and McClain C. R. , 1992: An overview of SeaWiFS and ocean color. NASA Tech. Memo. 104566, Vol. 1, 28 pp.
Kratz, D. P., Priestley K. J. , and Green R. N. , 2002: Establishing the relationship between the CERES window channel and total channel measured radiances for conditions involving deep convective clouds at night. J. Geophys. Res., 107 , 4245. doi:10.1029/2001JD001170.
Loeb, N. G., 2004: Four years of Terra SSF fluxes and clouds (CERES science team presentation). [Available online at http://science.larc.nasa.gov/ceres/STM/2004-11/loeb.pdf].
Loeb, N. G., Priestley K. J. , Kratz D. P. , Geier E. B. , Green R. N. , Wielicki B. A. , Hinton R. O. , and Nolan S. K. , 2001: Determination of unfiltered radiances from the Clouds and the Earth’s Radiant Energy System instrument. J. Appl. Meteor., 40 , 822–835.
Loeb, N. G., Kato S. , Loukachine K. , Manalo-Smith N. , and Doelling D. D. R. , 2005: Angular distribution models for top-of-atmosphere radiative flux estimation from the Clouds and the Earth’s Radiant Energy System instrument on the Terra satellite. Part I: Methodology. J. Atmos. Oceanic Technol., 22 , 338–351.
Loeb, N. G., and Coauthors, 2007: Multi-instrument comparison of top-of-atmosphere reflected solar radiation. J. Climate, 20 , 575–591.
Matthews, G., 2008: Celestial body irradiance determination from an underfilled satellite radiometer: Application to albedo and thermal emission measurements of the Moon using CERES. Appl. Opt., 47 , 4981–4993.
Matthews, G., Priestley K. , and Spence P. , 2005a: Z-domain numerical filter for removal of thermistor bolometer slow mode transients. Earth Observing Systems X, J. J. Butler, Ed., International Society for Optical Engineering (SPIE Proceedings, Vol. 5882), 588213, doi:10.1117/12.613981.
Matthews, G., Priestley K. , Spence P. , Cooper D. , and Walikainen D. , 2005b: Compensation for spectral darkening of short wave optics occurring on the cloud’s and the Earth’s radiant energy system. Earth Observing Systems X, J. J. Butler, Ed., International Society for Optical Engineering (SPIE Proceedings, Vol. 5882), 588212; doi:10.1117/12.618972.
Matthews, G., Priestley K. , Loeb N. G. , Loukachine K. , Thomas S. , Walikainen D. , and Wielicki B. A. , 2006: Coloration determination of spectral darkening occurring on a broadband Earth observing radiometer: Application to Clouds and the Earth’s Radiant Energy System (CERES). Earth Observing Systems XI, J. J. Butler, Ed., International Society for Optical Engineering (SPIE Proceedings, Vol. 6296), 62960M, doi:10.1117/12.680884.
Matthews, G., Priestley K. , and Thomas S. , 2007a: Spectral balancing of a broadband Earth observing radiometer with co-aligned short wave channel to ensure accuracy and stability of broadband daytime outgoing long-wave radiance measurements: Application to CERES. Infrared Spaceborne Remote Sensing and Instrumentation XV, M. Strojnik-Scholl, Ed., International Society for Optical Engineering (SPIE Proceedings, Vol. 6678), 66781H, doi:10.1117/12.734492.
Matthews, G., Priestley K. , and Thomas S. , 2007b: Transfer of radiometric standards between multiple low earth orbit climate observing broadband radiometers: Application to CERES. Earth Observing Systems XII, J. J. Butler and J. Xiong, Eds., International Society for Optical Engineering (SPIE Proceedings, Vol. 6677), 66770I, doi:10.1117/12.734478.
Minnis, P., Garber D. P. , Young D. F. , Arduini R. F. , and Tokano Y. , 1998: Parameterizations of reflectance and emittance for satellite remote sensing of cloud properties. J. Atmos. Sci., 55 , 3313–3339.
NASA, cited. 2008a: CERES ES8 Terra Edition2 data quality summary. [Available online at http://eosweb.larc.nasa.gov/PRODOCS/ceres/ES8/Quality_Summaries/CER_ES8_Terra_Edition2.html].
NASA, cited. 2008b: CERES ES8 Aqua Edition2 data quality summary. [Available online at http://eosweb.larc.nasa.gov/PRODOCS/ceres/ES8/Quality_Summaries/CER_ES8_Aqua_Edition2.html].
Ohring, G., Wielicki B. A. , Spencer R. , Emery B. , and Datla R. , 2005: Satellite instrument calibration for measuring global climate change. Bull. Amer. Meteor. Soc., 86 , 1303–1313.
Salomonson, V. V., Barnes W. L. , Maymon P. W. , Montgomery H. E. , and Ostrow H. , 1989: MODIS: Advanced facility instrument for studies of the earth as a system. IEEE Trans. Geosci. Remote Sens., 27 , 145–153.
Simpson, J., Kummerow C. , Tao W. K. , and Adler R. F. , 1996: On the Tropical Rainfall Measuring Mission (TRMM). Meteor. Atmos. Phys., 60 , (1–3). 19–36.
Spence, P. L., Priestley K. J. , Kizer E. A. , Thomas S. , Cooper D. L. , and Walikainen D. R. , 2004: Correction of drifts in the measurements of the Clouds and the Earth’s Radiant Energy System scanning thermistor bolometer instruments on the Terra and Aqua satellites. Earth Observing Systems IX, W. L. Barnes and J. J. Butler, Eds., International Society for Optical Engineering (SPIE Proceedings, Vol. 5542), 53–64.
Weatherhead, E. C., and Coauthors, 1998: Factors affecting the detection of trends: Statistical considerations and applications to environmental data. J. Geophys. Res., 103 , (D14). 17149–17161.
Wielicki, B. A., and Green R. N. , 1989: Cloud identification for ERBE radiative flux retrieval. J. Appl. Meteor., 28 , 1133–1146.
Wielicki, B. A., Barkstrom B. R. , Harrison E. F. , Lee R. B. , Smith G. L. , and Cooper J. E. , 1996: Clouds and the Earth’s Radiant Energy System (CERES): An earth observing experiment. Bull. Amer. Meteor. Soc., 77 , 853–868.
(a) Drawing and (b) schematic of a CERES instrument, and (c) drawing of two CERES instruments operational on the same EOS platform.
Citation: Journal of Atmospheric and Oceanic Technology 26, 9; 10.1175/2009JTECHA1243.1
The three CERES channel spectral responses in comparison with scattered solar Lsol(λ) and emitted thermal Earth radiance Lth(λ).
Citation: Journal of Atmospheric and Oceanic Technology 26, 9; 10.1175/2009JTECHA1243.1
(a) Anomalous 2% drop in edition 2 SSF Terra clear-ocean SW flux in less than 4 yr. (b) Change in post-retrieval LDEF Suprasil transmission in comparison with clear ocean and SWICS lamp spectral radiance. (c) Terra ERBE-like percent direct comparison of near-simultaneous filtered SW radiance measurements indicating RAPS instrument always drops in response relative to its cross-track counterpart. (d) Terra Rev1 adjustments. (e) Table of Rev1 coefficients available on the Internet.
Citation: Journal of Atmospheric and Oceanic Technology 26, 9; 10.1175/2009JTECHA1243.1
(a) Ed2 SSF DCC albedo from all CERES instruments indicating SW optical degradation. (b) Ed2 Rev1 SSF DCC albedo from all CERES instruments indicating Terra overcorrection; Aqua undercorrection; and apparent ∼1% drop in SW flux between TRMM, Terra, and Aqua. (c) Test edition SSF DCC albedo from all CERES instruments showing universal placement on PFM SW radiometric scale and removal of all statistically significant trends.
Citation: Journal of Atmospheric and Oceanic Technology 26, 9; 10.1175/2009JTECHA1243.1
(a) Diagram of CERES telescope ram exposure during RAPS mode. (b) Space-bound particle mobilization of category A and B contaminant molecules to filtering optics within telescope during ram exposure. (c) Example (left) impulse and (right) impulse response of polymerized contaminant thickness in event of one-time deposition of category A and B molecules at mission start.
Citation: Journal of Atmospheric and Oceanic Technology 26, 9; 10.1175/2009JTECHA1243.1
Flow diagram summarizing the feedback iterative technique used to minimize ϒ [Eq. (14)].
Citation: Journal of Atmospheric and Oceanic Technology 26, 9; 10.1175/2009JTECHA1243.1
Test edition model estimates of (left) monthly contaminant arrival thickness on SW optics and (right) monthly polymerized absorbing contaminant thickness on SW optics.
Citation: Journal of Atmospheric and Oceanic Technology 26, 9; 10.1175/2009JTECHA1243.1
Test edition gain changes made for all five CERES instrument channels. The total and WN channel changes are determined from onboard blackbody calibrations, and the SW channel changes are determined from the contaminant transmission model and DCC albedo.
Citation: Journal of Atmospheric and Oceanic Technology 26, 9; 10.1175/2009JTECHA1243.1
(a)–(d) Spectral balancing metrics for all four CERES EOS instruments that tell of fractional changes in total channel solar response to DCC, clear-water, and clear-land scattered solar radiance. (e),(f) Required change to CERES total channels from ground calibration after 1 yr in orbit to match all three balancing metrics.
Citation: Journal of Atmospheric and Oceanic Technology 26, 9; 10.1175/2009JTECHA1243.1
(left) Mission life test edition changes to the (left) CERES SW and (right) CERES total spectral responses. Shaded plot is a typical all-sky MODTRAN scattered solar Earth spectrum.
Citation: Journal of Atmospheric and Oceanic Technology 26, 9; 10.1175/2009JTECHA1243.1
(a) Ed2, (b) Ed2 Rev1, and (c) test edition SSF percent direct compare of near-simultaneous unfiltered SW nadir Terra radiances.
Citation: Journal of Atmospheric and Oceanic Technology 26, 9; 10.1175/2009JTECHA1243.1
As in Fig. 11, but for Aqua.
Citation: Journal of Atmospheric and Oceanic Technology 26, 9; 10.1175/2009JTECHA1243.1
(a) Ed2 and (b) test edition SSF percent direct compare of near-simultaneous unfiltered night LW nadir Terra radiances. (c) Ed2 and (d) test edition SSF percent direct comparisons of near-simultaneous unfiltered day LW nadir Terra radiances.
Citation: Journal of Atmospheric and Oceanic Technology 26, 9; 10.1175/2009JTECHA1243.1
As in Fig. 13, but for Aqua.
Citation: Journal of Atmospheric and Oceanic Technology 26, 9; 10.1175/2009JTECHA1243.1
(a) Ed2 and (b) test edition SSF percent direct compare of near-simultaneous unfiltered night WN nadir Terra radiances. (c) Ed2 and (d) test edition SSF percent direct compare of near-simultaneous unfiltered night WN nadir Aqua radiances.
Citation: Journal of Atmospheric and Oceanic Technology 26, 9; 10.1175/2009JTECHA1243.1
PFM test edition percent changes from edition 2 (SSF) for (a) SW, (b) WN, (c) day LW, and (d) night LW.
Citation: Journal of Atmospheric and Oceanic Technology 26, 9; 10.1175/2009JTECHA1243.1
FM1 test edition percent changes from edition 2 (SSF) for (a) SW, (b) WN, (c) day LW, and (d) night LW. (e)–(h) As in (a)–(d), but for FM2.
Citation: Journal of Atmospheric and Oceanic Technology 26, 9; 10.1175/2009JTECHA1243.1
As in Fig. 17, but for (a)–(d) FM3 and (e)–(h) FM4.
Citation: Journal of Atmospheric and Oceanic Technology 26, 9; 10.1175/2009JTECHA1243.1
(a) Sensitivity study determining drifts in CERES DCC albedo for 1% drifts in SSF cloud retrievals. Predictions of (b) Terra, (c) Aqua, and (d) FM5 calibration drifts using test edition methodology combined with lunar calibration data.
Citation: Journal of Atmospheric and Oceanic Technology 26, 9; 10.1175/2009JTECHA1243.1
DCC albedo trends in percent decade−1 with ±95% confidence intervals in parentheses.
Estimates of smallest climate signal currently detectable to 95% confidence using test edition calibration through December 2006 in percent per decade with the smallest signal detectable given 15 yr of data combined with lunar scans in parenthesis.