Observing Condition Constraints (in use pre-August 2002)

This out-of-date page will remain available indefinitely but is no longer maintained.

All queue-mode observations must have observing condition constraints specified by the proposer which describe the minimum (i.e. poorest) conditions under which the observation should be executed. Classical programmes generally need only specify the sky background constraint (and even then it is usually relevant only for optical observations), however the information presented here is useful as a guide of what conditions and performance visiting observers can expect. The observing condition constraints must be specified in the Phase I proposal to avoid loading the queue entirely with one type of conditions (e.g. best image quality).

Caveat: the characteristics of the conditions described here are estimates based on our best-guess performance models of the telescope systems and site conditions. The values are subject to change. An important aspect of telescope commissioning will be to verify and, if necessary, update these models.

The constraints are divided into five categories (if appropriate, values for Mauna Kea and Cerro Pachon are given separately):

• Image quality
• Sky transparency (cloud cover)
• Sky transparency (water vapour content)
• Sky and telescope background
• Air mass (zenith distance)

The specific properties corresponding to these categories usually are wavelength dependent and will not be relevant for all observations. For example, the sky background at visible wavelengths is dominated by the lunar phase and moon-to-target angle, at near-IR wavelengths by telluric OH line emission and at thermal-IR wavelengths by the total column of water vapour above the observatory. For the image quality, sky transparency and background we have chosen to represent the variation in these conditions (which is deterministic in the case of visible sky brightness, statistical in the case of water vapour column, for example) by a percentile representing the frequency of occurrence of the specific property. Observing constraints are specified in terms of these percentiles (see examples below) e.g. (best) 20%-ile, 50%-ile (better than median) etc.

This page provide a translation between the frequency of occurrence and the specific value for the relevant property as well as further information and guidance on their use by observers. The emphasis is on providing observers with these constraints in meaningful units (and corresponding to those used in the integration time calculator) as well as indicating their likelihood.

Temporal constraints, e.g. for time-critical observations or periodic monitoring, and GMOS-specific constraints (such as those which affect mask cutting) are (to be) described elsewhere.

Several examples serve to illustrate how the specific scientific objectives of a program might affect the users choice of constraints:

1. example - NIRI spectroscopy of an extended object
2. example - NIRI imaging of structure within an extended object

Image Quality (non-AO) - MK and CP

Note that these values apply to the telescope pointing at zenith. The performance degradation away from the zenith can be approximated crudely as (air mass)^0.6. The links in the table (to more details) provides more specific information.

Explanation of table entries:

1. Numerical values in the constraint columns are the current estimate of delivered image quality, defined as the 50% encircled energy diameter in arcsec, in the telescope focal plane at the specified wavelengths. These values are expected to improve as thermal control of the facility is optimised. The 50% EED is equal to the full width at half maximum for a Gaussian profile.
2. "Any" means that the observation can be scheduled under any image quality conditions. At optical and near-IR wavelength the image quality distribution has a long (non-Gaussian) tail. The values quoted are typical of the poorest conditions.
3. Use of wavefront sensors for image motion compensation (fast guiding) is required. For most wavelengths, values for peripheral and on-instrument WFSs are given. In all cases the use of the PWFS for closed-loop primary mirror figure (aO) correction is assumed.
4. See the specific instrument pages for descriptions of the wavefront sensors required or available for use with each instrument. In this table it is assumed that the WFS star is slightly brighter than the 'knee' in the WFS performance curve (follow the links in the table for more details).
5. Estimates of the AO-corrected image quality are described elsewhere (e.g. see the Hokupa'a pages).

Note that the relevant parameter here is image quality and not simply seeing, that is, a wind speed distribution and the telescope performance (e.g. windshake, servo and wavefront sensor characteristics) have been incorporated into the analysis. The model was adapted by Mark Chun from original Mathematica calculations by Charles Jenkins (see also Jenkins 1998, MNRAS, 294, 69). A more detailed level of analysis, including the dependencies on zenith distance, guide star magnitude and guide star off-axis angle, from which the summary table was generated, is available by clicking on more details in the table.

Interpretation of the table is shown in the following example. An image at K of a target at zenith with a bright guide star in the Peripheral Wavefront Sensor would be expected to have a 50% EED of no more than 0.30 arcsec 20% of the time and no more than 0.40 arcsec 50% of the time.

Sky Transparency (Cloud Cover) - MK and CP

Explanation of table entries:

1. The percentiles are based on long-term data for Mauna Kea and corresponding to fractions of the usable time.
2. "Photometric"  - cloudless and capable of delivery stable flux.
3. "Low sky noise" - photometric and having low sky noise fluctuation. (Note that the sky noise is yet to be characterised).
4. "Cloudless" - no clouds but relatively high sky noise.
5. "Patchy cloud" - relatively transparent patches amongst thicker cloud. For the purpose of integration time calculation it is assumed that clearer patches have a transmission that is poorer by 0.3 mag than the nominal atmospheric extinction and is variable.
6. "Cloudy" - cloud cover over essentially the whole sky. For the purpose of integration time calculation it is assumed that the transmission is poorer by 2 mag than the nominal atmospheric extinction and is variable. The increase in background makes these conditions unusable at thermal infrared wavelengths.
7. "Usable" - any conditions under which the telescope is open. The increase in background makes these conditions unusable at thermal infrared wavelengths. For the purpose of integration time calculation it is assumed that the transmission is poorer by 3 mag than the nominal atmospheric extinction.

Sky Transparency (Water Vapour) - MK

Sky Transparency (Water Vapour) - CP

Explanation of table entries:

1. In the integration time calculator the optical transparency is derived from model transmission spectra. See "Sky Transparency (cloud cover)" for a related constraint.
2. Near- and mid-IR transparencies are characterised by the precipitable water vapour content (in mm) derived from the 225GHz zenith optical depth. The atmospheric absorption is strongly wavelength dependent as shown in model transmission spectra. 
3. Percentiles are based on long-term data for Mauna Kea and 1992-1994 data from the ESO/VLT site at Cerro Paranal. Note, that in Chile the water vapour content in summer (Jan-Mar) can be considerably higher than the average (5-10mm) as shown clearly on this 1999 data from the future ALMA site. The Mauna Kea data do not show a strong seasonal variation.  
4. "Any" means that the observation can be scheduled under any conditions.

Caution: observations at thermal IR wavelengths should use the same constraint for sky transparency (water vapour) and for sky background, otherwise the tighter of the two constraints will be used when scheduling.

Sky Background - MK

Sky Background - CP

Explanation of joint table entries:

1. All values pertain to the zenith.
2. Optical background values originate from a Monte Carlo simulation of the sky brightness using a model which includes scattered moonlight and zodiacal light, and pertains to high ecliptic latitude. The sky colour is different between constraint bins. Crudely speaking, the moon is below the horizon during about one half of queue-mode hours. These tabulated values are used to scale an empirical sky spectrum within the integration time calculator. This is the only observing condition constraint required for classically-scheduled observing.
3. The near-infrared  J- and H-band backgrounds are dominated by OH airglow lines. The K-band comprises both OH and thermal emission. Within the integration time calculator the background is assumed to be constant (once the sun is sufficiently below the horizon) even though the OH component is known to vary during the night (more details).
4. The thermal IR (3-25µm) background is characterised by the precipitable water vapour content (in mm) derived from the 225GHz zenith optical depth. The atmospheric emission is strongly wavelength dependent (more details). Percentiles are based on the water vapour data shown above. In transparent regions, the background will also vary with ambient temperature (to be characterised).
5. "Any" means that the observation can be scheduled under any conditions.

Caution: thermal IR observations should use the same constraint for sky transparency (water vapour) and for sky background, otherwise the tighter of the two constraints will be applied when scheduling.

Air Mass

This constraint (not used in Phase I proposals, but used in Phase II) defines the maximum air mass [= sec(zenith distance) = 1/cos(zd)] at which the target should be observed. The air mass affects the sky transparency (e.g. the general atmospheric extinction as well as the depth and breadth of specific absorption bands due to atmospheric constituents such as water vapour and CO₂), sky brightness and image quality. As a crude first approximation, the sky transparency and brightness each become poorer in proportion to the increase in air mass (e.g. sky brightness is twice as great at air mass = 2 than at air mass = 1) and the image quality degrades as (air mass)^0.6.

Last update February 23, 2002; Phil Puxley and Bernadette Rodgers