1. Students as Ground Observers for Satellite Cloud Retrieval Validation 13th Conference on Satellite Meteorology & Oceanography Norfolk, VA Sept. 2004 Lin H. Chambers, P. Kay Costulis, David F. Young NASA Langley Research Center, Hampton, VA Tina M. Rogerson Science Applications International Corporation, Hampton, VA

2. OUTLINE Sources of student data What is the S’COOL Project? Comparisons –Proof of Concept –New Comparisons –Bright Surfaces Conclusions

3. Sources of Student Data  The CERES S’COOL Project –More than 35,000 complete observations –9,172 now have corresponding CERES data –http://scool.larc.nasa.gov The GLOBE Program –More than 2.5 M cloud data points –http://www.globe.gov

4. What is S’COOL? Began Jan. 1997 Students’ Cloud Observations On-Line K-12 Education and outreach portion of CERES: Clouds and the Earth's Radiant Energy System 1700+ participants in 65 countries Focused on obtaining ground-based cloud observations for validation of the CERES data

5. The S’COOL Concept Students provide ground observations for CERES overpass 1. Determine satellite overpass time 2. Observe cloud properties 3. Transmit results to NASA 4. Compare to satellite-retrieved properties Data of value to CERES scientists Real-world learning for students

6. Data Collected Cloud type Contrails Cloud cover Visual opacity Surface Cover Surface Measurements Comments

7. Comparing to Satellite S’COOL Site Matched to 1 degree Satellite Region Observation Times Within 15 Minutes

8. FIRST S’COOL Comparison Cloud Observations Over Gloucester, VA January 13 & 17, 1997

9. Initial Comparisons: Proof of Concept Measurements in 1998 CERES on TRMM only (~50 correspondences) Augmented with AVHRR and geostationary data (~50): Analyzed by hand

10. Cloud Amount Comparison 62% in complete agreement 0% in complete disagreement Stats: Chi-Squared value of 82; significant to 5e-12

11. Cloud Layer Comparison

12. Interim Conclusions Clearly some useful information Insight into cloud layering Insight into sparse, thin cirrus Educationally a big success

13. New Comparisons - 2004 New CERES angular models (see talk by Loeb this afternoon) CERES on TRMM, Terra, Aqua Feb. 1998 to April 2004 Production data products

14. Data Available Max: 479 (High School in Pennsylvania) Min: 1 (70 schools)

15. Cloud Amount Comparison 54.5% in complete agreement 2% in complete disagreement Stats: Chi-Squared value of 5636; significant!!!

16. Students Overcast vs. Satellite Clear (48 cases) Spatial Mismatch?: >1/3 are schools located less than 0.1 degree from the edge of a lat/long grid box. Universal Time?: 3 cases with incorrect UT Student/Satellite error?: remaining cases have no clear explanation. Study needed. Snow: 10 cases, yet the satellite still reports clear sky.

17. Students Clear vs. Satellite Overcast (143 cases) Spatial mismatch?: About 22% Universal Time?: ~10 Snow?: 18 cases students report snow. Only one satellite retrieval is suspect: low cloud temperature 2.5K below the surface temperature. Satellite/Student error?: stratus = clear?

18. Cloud Amount Comparison 191 3-class errors (2%) - ~1/3 easily explainable 711 2-class errors (8%) - need more study 3271 1-class errors (36%) - may be near-matches

19. First look at 1-class errors 24% of CERES has 5 < f c < 10 20% of CERES has 10 < f c < 15 Students say 0-5% cloud Satellite says 5-50% cloud

20. Subvisual Cirrus? MODIS vs GLOBE cloud type comparison indicated some subvisual cirrus (Stephens and Rogers, 2004). This CERES/S’COOL dataset: 19 cases where  tot < 3 None high cloud only 5 cases where  tot < 1 None high clouds No evidence of subvisual cirrus in this dataset May be due to location of the S’COOL student data, over land with few data points in the Tropics.

21. Cloud Layer Comparison

22. Effect of Bright Surfaces 1057 reports (~11%) with snow or ice in ground report Data from 1/4 of respondents Max - 86 (4th grade in NH) Min - 1 (31 schools)

23. Snow Effect on Cloud Amount All Ground Observers ClrPCMCOV SATSAT Clr141535010148 PC624897575230 MC193553695680 OV1431874891992 Snow/Ice Ground Observers ClrPCMCOV SATSAT Clr14727810 PC67753519 MC35596895 OV183352309 Chi-squared = 671

24. Snow Effect on Cloud Amount All - scaled Ground Observers ClrPCMCOV SATSAT Clr 16340126 PC 721036627 MC 22648078 OV 162256230 Snow/Ice Ground Observers ClrPCMCOV SATSAT Clr14727810 PC67753519 MC35596895 OV183352309

25. Snow Effect on Cloud Layers All Ground Observers No Cloud 1-layerMulti- layer SATSAT No Cld 950615100 1-layer 3062030581 Multi 24933061035 Snow/Ice Ground Observers No Cloud 1-layerMulti- layer SATSAT No Cld92735 1-layer4229554 Multi3140065

26. Snow Effect on Cloud Layers All - scaled Ground Observers No Cloud 1-layerMulti- layer SATSAT No Cld 1107112 1-layer 3523567 Multi 29383120 Snow/Ice Ground Observers No Cloud 1-layerMulti- layer SATSAT No Cld92735 1-layer4229554 Multi3140065

27. Conclusions First major analysis of student ground observer data to validate cloud retrievals from a satellite instrument. A few pitfalls are evident. Useful information can be derived.

28. Future Plans Inviting S’COOL participants to do detailed analysis of their correspondences More analysis to be done (2-class and 1-class errors, cloud levels, opacity….) Data available via the Internet for analysis: http://asd-www.larc.nasa.gov/SCOOL/usedata.html

29. Acknowledgments Science and Education support from NASA’s Earth Science Enterprise. This work would not be possible without the participation of our extended network of educators and their students, and we thank them most sincerely for their efforts.