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WFC3 Data Handbook > Chapter 7: WFC3/IR Sources of Error > 7.10 Time Variable Background Contamination

7.10
7.10.1 Scattered Earthlight
For certain HST orientations, the WFC3/IR detector can be subject to elevated and/or irregular background levels. Observations made when HST is pointing near the bright Earth limb can result in the leftmost ~200 columns of the detector being subjected to background levels up to twice as bright as that on the rest of the chip. This is due to scattered Earth light. Figure 7.11 shows an example of this behavior. The overall shape of this high background region is very similar from one affected image to another, but the brightness of the scattered light varies as the HST pointing approaches or recedes from the bright Earth limb. Details on the nature of this effect in IR darks can be found in WFC3 ISR 2009-21. This effect can often be present for observations made when the limb angle, which is the angle between HST's pointing direction and the nearest limb of the bright Earth, is less than ~30 degrees.
Figure 7.11: IR Image affected by scattered earth-shine.
7.10.2 Metastable Helium 1.083 μm Emission Line
An additional source of background contamination is caused by the He line at 1.083 μm. Filters whose bandpasses contain this He line are F105W, F110W and the G102 grism. The emission line originates from metastable helium in the Earth’s upper atmosphere which, when present, can increase the IR background by up to factors of 6 above the nominal zodiacal background. This spatially diffuse source affects portions of HST orbits where both the telescope and the atmosphere are illuminated by sunlight. WFC3 ISR 2014-03 describes this effect more fully while WFC3 ISR 2016-16 provides mitigation strategies (summarized in the next section).
7.10.3 Time-variable IR Background Mitigation Strategies
Strong time variation in the background can corrupt the wf3ir cosmic-ray identification algorithm (CRCORR, Section 3.3.9), which assumes that a given pixel sees a constant count rate from the combination of sources and diffuse background (i.e., the "ramps" are linear). Strong time variation in the background can trip the CR thresholds, with most or all of the image identified as a CR at a given read. Furthermore, since the background variation is fairly smooth from read to read any algorithm that tries to iteratively identify clean reads before and after a CR hit will likely fail.
The primary impact of the strong background variations is to increase noise as it reduces the available exposure time in the final flt products (e.g. only one or two reads out of 15 are used to form the flt). Furthermore, the distribution of background pixel values frequently shows multi-modal non-Gaussian shapes as different parts of the image trip and confuse the CR algorithm in different ways ( Figure 7.12).
Figure 7.12: Comparison of a pair of back-to-back F105W exposures where the first exposure (left) showed a constant zodiacal light background and the Helium line background increased rapidly over the duration of the second exposure (center column). The pixel distribution of the second exposure is poorly behaved (right): the noise is not simply higher due to the elevated background level but it also shows a bimodal non-Gaussian structure. Exposures such as these should either be discarded or reprocessed, for example, with strategies outlined in WFC3 ISR 2016-16. The bottom panels show the same images and pixel distributions for images which have been reprocessed via wf3ir using CRCORR=OMIT. The noise properties of the products are better behaved but the cosmic rays must now be identified by other means.
WFC3 ISR 2016-16 provides more detail on how to identify exposures affected by these time-variable backgrounds as well as suggestions for reprocessing the affected exposures. The most straightforward strategy is to simply treat the WFC3/IR detector like a standard CCD and take the final read as the measure of the total flux accumulated during the exposure. This strategy is insensitive to any background variations during the exposure, but requires the user to then identify CRs by other means, for example, comparing dithered exposures with AstroDrizzle. WFC3 ISR 2016-16 also provides a hybrid algorithm for removing the time variation of the background while still performing the CR identification within the wf3ir pipeline.

WFC3 Data Handbook > Chapter 7: WFC3/IR Sources of Error > 7.10 Time Variable Background Contamination

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