CERES S'COOL PROJECT UPDATE: The Evolution and Value of a Long-Running Education Project with a Foundation in NASA Earth Science Missions

Abstract

Since 1997, S'COOL has engaged interested participants worldwide in observing clouds and comparing data from ground and satellite sources to inform validation efforts for several NASA Earth science missions.

Fig. 1.

History of S’COOL participation: (a) Number of new participants that registered for the S’COOL Project each year. (b) Number of ground observations submitted by fixed site participants (solid black line), and subset that coincides with CERES satellite cloud retrieval data (dashed black line). Observations and subset coinciding with satellite data from Rovers are also shown (solid and dashed blue lines). Note that 2016 data, available through the month of May, was extrapolated for comparison to past years.

Fig. 2.

S’COOL Project participation spans the globe. Colored icons, plotted from least to most observations, show total observations at each location since the beginning of the project, increasing from blue to red. Diamonds (circles) represent locations where ≥60% (<60%) of observations correspond to satellite data. (An up-to-date version of this map may be found at http://scool.larc.nasa.gov/background-latestmap.html.)

Fig. 3.

S’COOL and Rover amount and length of observations. (a) Histogram showing the distribution of observers by number of observations reported; (b) distribution by length of participation (from first to last observation). Some observers report more than one observation on a single day.

Fig. 4.

A sample of the ground and satellite comparison visualization that S’COOL participants receive when their observation report corresponds to a satellite overpass. This example aligns to both GEO and CERES overpasses. Readers may explore many more reports at https://scool.larc.nasa.gov/en_query_alldata.html. (a) Reported ground observation. (b) Corresponding satellite retrieved cloud properties. (c) Submitted ground photo. (d) Corresponding satellite imagery—in this case a GEO image centered on the observer’s location, and links to the corresponding MODIS image (in both Rapid Response and Worldview). Also shown is a link to a similar visualization (CERES Terra Match) for CERES rather than GEO.

Fig. 5.

Frequency of occurrence for each cloud type reported by S’COOL observers when the CERES algorithm failed to detect any clouds present. Cirrus (and other cirroform) and cumulus clouds are the most frequently missed cloud types.

Fig. 6.

The CERES MODIS optical depth retrieval distribution as a function of the three S’COOL observer cloud opacity categories: (a) opaque, (b) translucent, and (c) transparent. On average, observers are correctly classifying opacity: the mean optical depth ($\overline{\tau }$) decreases and the peak in percent occurrence shifts toward a lower optical depth value from (a) to (c). The peak at >50 optical depth for the transparent and translucent categories is an artifact of the matching process and does not reflect a deficiency in observer skill.

Fig. 7.

CCGL cloud mask (blue = sky; white = cloud) overlaid with a collocated S’COOL observation. The hatched overlay indicates the cloud height category reported by the S’COOL observer. (a) A case where the S’COOL observer accurately reported a single high cloud layer. (b) A case where the S’COOL observers were unable to see the CCGL-detected cloud layers above the low-level cloud they reported due to the high opacity and overcast coverage of the low-level cloud. Similarly, a passive satellite instrument would see only the top layer.

Fig. SB1.

The cover of the Jun 2003 issue of BAMS [containing Chambers et al. (2003)] featured four very young S’COOL participants: kindergarten students at Saint James School in Falls Church, Virginia.