WorkswithlidarModels(data orfashion)Has beento thePacificOceanPlays amusicalinstrumentDoeslakescienceClimberknows 3TaylorSwiftsongsHas workedin a cleanlab (on landor on a ship)Hasconsideredbecomingan astronautMovedhousewithin thelast yearDoes alot ofoutreachHas useda weatherballoonFliesdronesLives >2hoursdrive tothe oceanIshungryright nowWorkswithradarKnowswhat asundog isHas beento theAtlanticOceanKnowswhat asundog isHas doneairbornescienceStarwarsfanDid fieldwork inthe lastyearHasa dogDoes adistancesportHasinteractedwith a CTD-RosetteDoesnot likepizzaWriteswikipediaarticlesScubadivesKnows amagictrickHas aGitHubCan tell afield workdisasterstoryHas beenat sea for>1 weekKnows moreaboutpolarimetrythan owningthe sunglassesHas beento aconcert inlast monthHas beenat sea for>1 weekPrefersto codein pythonHas called intoa PACEScience &ApplicationsTeam (SAT)MeetingDrove acar >1hour toget hereWorkswithcitizenscientistsPlays amusicalinstrumentSpeaks>2languagesDoesNOT liketo teachbut has toHas beento theArcticOceanPrefers tocode inMATLABFilters alot ofseawaterIs anatmosphericscientistLovesaerosolsPrefersto codein RFlewhere ona planeHas used asun-photometerHasa catDogpersonHas beento theSouthernOceanWorkswithlidarModels(data orfashion)Has beento thePacificOceanPlays amusicalinstrumentDoeslakescienceClimberknows 3TaylorSwiftsongsHas workedin a cleanlab (on landor on a ship)Hasconsideredbecomingan astronautMovedhousewithin thelast yearDoes alot ofoutreachHas useda weatherballoonFliesdronesLives >2hoursdrive tothe oceanIshungryright nowWorkswithradarKnowswhat asundog isHas beento theAtlanticOceanKnowswhat asundog isHas doneairbornescienceStarwarsfanDid fieldwork inthe lastyearHasa dogDoes adistancesportHasinteractedwith a CTD-RosetteDoesnot likepizzaWriteswikipediaarticlesScubadivesKnows amagictrickHas aGitHubCan tell afield workdisasterstoryHas beenat sea for>1 weekKnows moreaboutpolarimetrythan owningthe sunglassesHas beento aconcert inlast monthHas beenat sea for>1 weekPrefersto codein pythonHas called intoa PACEScience &ApplicationsTeam (SAT)MeetingDrove acar >1hour toget hereWorkswithcitizenscientistsPlays amusicalinstrumentSpeaks>2languagesDoesNOT liketo teachbut has toHas beento theArcticOceanPrefers tocode inMATLABFilters alot ofseawaterIs anatmosphericscientistLovesaerosolsPrefersto codein RFlewhere ona planeHas used asun-photometerHasa catDogpersonHas beento theSouthernOcean

Human Bingo: Find someone who... - Call List

(Print) Use this randomly generated list as your call list when playing the game. There is no need to say the BINGO column name. Place some kind of mark (like an X, a checkmark, a dot, tally mark, etc) on each cell as you announce it, to keep track. You can also cut out each item, place them in a bag and pull words from the bag.


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  1. Works with lidar
  2. Models (data or fashion)
  3. Has been to the Pacific Ocean
  4. Plays a musical instrument
  5. Does lake science
  6. Climber
  7. knows 3 Taylor Swift songs
  8. Has worked in a clean lab (on land or on a ship)
  9. Has considered becoming an astronaut
  10. Moved house within the last year
  11. Does a lot of outreach
  12. Has used a weather balloon
  13. Flies drones
  14. Lives >2 hours drive to the ocean
  15. Is hungry right now
  16. Works with radar
  17. Knows what a sundog is
  18. Has been to the Atlantic Ocean
  19. Knows what a sundog is
  20. Has done airborne science
  21. Star wars fan
  22. Did field work in the last year
  23. Has a dog
  24. Does a distance sport
  25. Has interacted with a CTD-Rosette
  26. Does not like pizza
  27. Writes wikipedia articles
  28. Scuba dives
  29. Knows a magic trick
  30. Has a GitHub
  31. Can tell a field work disaster story
  32. Has been at sea for >1 week
  33. Knows more about polarimetry than owning the sunglasses
  34. Has been to a concert in last month
  35. Has been at sea for >1 week
  36. Prefers to code in python
  37. Has called into a PACE Science & Applications Team (SAT) Meeting
  38. Drove a car >1 hour to get here
  39. Works with citizen scientists
  40. Plays a musical instrument
  41. Speaks >2 languages
  42. Does NOT like to teach but has to
  43. Has been to the Arctic Ocean
  44. Prefers to code in MATLAB
  45. Filters a lot of seawater
  46. Is an atmospheric scientist
  47. Loves aerosols
  48. Prefers to code in R
  49. Flew here on a plane
  50. Has used a sun-photometer
  51. Has a cat
  52. Dog person
  53. Has been to the Southern Ocean