S. L. Lawson

Evidence for water ice near the lunar poles

Improved versions of Lunar Prospector thermal and epithermal neutron data were studied to help discriminate between potential delivery and retention mechanisms for hydrogen on the Moon. Improved spatial resolution at both poles shows that the largest concentrations of hydrogen overlay regions in permanent shade. In the north these regions consist of a heavily cratered terrain containing many small (less than ∼10-km diameter), isolated craters. These border circular areas of hydrogen abundance ([H]) that is only modestly enhanced above the average equatorial value but that falls within large, flat-bottomed, and sunlit polar craters. Near the south pole, [H] is enhanced within several 30-km-scale craters that are in permanent shade but is only modestly enhanced within their sunlit neighbors. We show that delivery by the solar wind cannot account for these observations because the diffusivity of hydrogen at the temperatures within both sunlit and permanently shaded craters near both poles is sufficiently low that a solar wind origin cannot explain their differences. We conclude that a significant portion of the enhanced hydrogen near both poles is most likely in the form of water molecules.

Brightness temperatures of the lunar surface: Calibration and global analysis of the Clementine long‐wave infrared camera data

The scientific payload on the Clementine spacecraft included a long-wave infrared (LWIR) camera with a single passband centered at a wavelength of 8.75 μm. The Clementine orbit deviated by ±30° from Sun synchronous, and for two lunar months, dayside nadir-looking images were obtained near local noon. During the systematic mapping phase of the Clementine mission, approximately 220,000 thermal-infrared images of the lunar surface were obtained. We have completed the calibration of the LWIR camera. Here we present the various steps involved in the calibration routine and the associated uncertainty analysis. The LWIR calibration routine can be outlined as follows: convert measured data number values to radiance via a calibration equation; subtract a zero-flux background image from each lunar image; divide by a flatfield frame; identify bad pixels; smooth over only bad pixels; adjust radiances to reflect the absolute calibration; and convert radiances to brightness temperatures via the Planck function. Observed LWIR radiances can be converted to brightness temperatures, which provide information on various physical properties of the lunar surface. We also present here the LWIR global data set. The LWIR data from noontime orbits demonstrate that the Lambertian temperature model of cos1/4(i) is a fair approximation for nadir-looking temperatures, rather than the cos1/6(i) behavior observed for ground-based measurements of the full Moon. Deviations from the Lambertian model are likely due to surface roughness effects and variations in infrared emissivity. In addition, the LWIR global data set reveals the dayside lunar thermal emission to be largely governed by albedo and by the solar incidence angle.

Lunar surface thermophysical properties derived from Clementine LWIR and UVVIS images

In an effort to understand the influence of albedo and large-scale topography on remote lunar surface measurements, we investigate the relationship between measured Clementine long-wave infrared (LWIR) camera temperatures and ultraviolet-visible (UVVIS) camera 750-nm reflectances. We compare the observed temperature-reflectance relationships with those predicted using a rough-surface numerical model with varying albedo. The lunar surface response in different highland and mare locations is explored as a function of varying phase angle. At very low phase angles the temperature and reflectance response is primarily governed by the variation in single-scattering albedo regardless of the presence of topography. As the phase angle increases, the influence of surface roughness grows. Finally, at moderate to high phase angles the effect of surface roughness dominates. In the absence of large-scale topography the lunar surface temperature and reflectance response at all phase angles is governed by the variation in single-scattering albedo. LWIR-measured temperature variations yield local topographic information at high incidence angles that is unavailable via the reflectance, while UVVIS-measured reflectance variations yield local topographic information at low incidence angles that is unavailable via the temperature.

An imaging radiometer for measurement of lunar polar cold trap temperatures

The LRO Radiometer Investigation is an experiment proposed for NASA’s Lunar Reconnaisance Orbiter mission that will use a simple but extremely sensitive radiometer to measure the temperatures of the region of permanent shade at the lunar poles. Temperature governs the ability of these surfaces to act as cold traps, and tightly constrains the identity and lifetimes of potential volatile resources. The LRO Radiometer will also measure the night time temperature of the Moon, and use the extensive modeling experience of the team to use these data to produce maps of meter-scale rocks that constitute a significant hazard to landing and operations. The LRO Radiometer also supports LRO objectives by measuring the global abundance of meter scale rocks at 1 km resolution. This measurement is accomplished in four (4) months of observations.

LANL MTI science team experience

The Multispectral Thermal Imager (MTI) is a technology test and demonstration satellite whose primary mission involved a finite number of technical objectives. MTI was not designed, or supported, to become a general purpose operational satellite. The role of the MTI science team is to provide a core group of system-expert scientists who perform the scientific development and technical evaluations needed to meet programmatic objectives. Another mission for the team is to develop algorithms to provide atmospheric compensation and quantitative retrieval of surface parameters to a relatively small community of MTI users. Finally, the science team responds and adjusts to unanticipated events in the life of the satellite. Broad or general lessons learned include the value of working closely with the people who perform the calibration of the data as well as those providing archived image and retrieval products. Close interaction between the Los Alamos National Laboratory (LANL) teams was very beneficial to the overall effort as well as the science effort. Secondly, as time goes on we make increasing use of gridded global atmospheric data sets which are products of global weather model data assimilation schemes. The Global Data Assimilation System information is available globally every six hours and the Rapid Update Cycle products are available over much of the North America and its coastal regions every hour. Additionally, we did not anticipate the quantity of validation data or time needed for thorough algorithm validation. Original validation plans called for a small number of intensive validation campaigns soon after launch. One or two intense validation campaigns are needed but are not sufficient to define performance over a range of conditions or for diagnosis of deviations between ground and satellite products. It took more than a year to accumulate a good set of validation data. With regard to the specific programmatic objectives, we feel that we can do a reasonable job on retrieving surface water temperatures well within the 1°C objective under good observing conditions. Before the loss of the onboard calibration system, sea surface retrievals were usually within 0.5°C. After that, the retrievals are usually within 0.8°C during the day and 0.5°C at night. Daytime atmospheric water vapor retrievals have a scatter that was anticipated: within 20%. However, there is error in using the Aerosol Robotic Network retrievals as validation data which may be due to some combination of calibration uncertainties, errors in the ground retrievals, the method of comparison, and incomplete physics. Calibration of top-of-atmosphere radiance measurements to surface reflectance has proven daunting. We are not alone here: it is a difficult problem to solve generally and the main issue is proper compensation for aerosol effects. Getting good reflectance validation data over a number of sites has proven difficult but, when assumptions are met, the algorithm usually performs quite well. Aerosol retrievals for off-nadir views seem to perform better than near-nadir views and the reason for this is under investigation. Land surface temperature retrieval and temperature-emissivity separations are difficult to perform accurately with multispectral sensors. An interactive cloud masking system was implemented for production use. Clouds are so spectrally and spatially variable that users are encouraged to carefully evaluate the delivered mask for their own needs. The same is true for the water mask. This mask is generated from a spectral index that works well for deep, clear water, but there is much variability in water spectral reflectance inland and along coasts. The value of the second-look maneuvers has not yet been fully or systematically evaluated. Early experiences indicated that the original intentions have marginal value for MTI objectives, but potentially important new ideas have been developed. Image registration (the alignment of data from different focal planes) and band-to-band registration has been a difficult problem to solve, at least for mass production of the images in a processing pipeline. The problems, and their solutions, are described in another paper.