LovesaerosolsHas called intoa PACEScience &ApplicationsTeam (SAT)MeetingHas beento thePacificOceanHas beento theAtlanticOceanFilters alot ofseawaterModels(data orfashion)Speaks>2languagesHas doneairbornescienceDoesNOT liketo teachbut has toHasinteractedwith a CTD-Rosetteknows 3TaylorSwiftsongsHas beenat sea for>1 weekHas beento theSouthernOceanMovedhousewithin thelast yearFliesdronesHas beenat sea for>1 weekWriteswikipediaarticlesKnowswhat asundog isKnows moreaboutpolarimetrythan owningthe sunglassesHasa dogDoes alot ofoutreachHas beento theArcticOceanPlays amusicalinstrumentCan tell afield workdisasterstoryPrefersto codein pythonPlays amusicalinstrumentHas aGitHubDoes adistancesportDogpersonHas beento aconcert inlast monthWorkswithlidarDoeslakescienceScubadivesHasa catIs anatmosphericscientistDoesnot likepizzaLives >2hoursdrive tothe oceanStarwarsfanFilters alot ofseawaterIshungryright nowHasconsideredbecomingan astronautKnows amagictrickPrefersto codein RWorkswithradarDrove acar >1hour toget hereFlewhere ona planeHas workedin a cleanlab (on landor on a ship)WorkswithcitizenscientistsClimberDid fieldwork inthe lastyearPrefers tocode inMATLABHas useda weatherballoonHas used asun-photometerLovesaerosolsHas called intoa PACEScience &ApplicationsTeam (SAT)MeetingHas beento thePacificOceanHas beento theAtlanticOceanFilters alot ofseawaterModels(data orfashion)Speaks>2languagesHas doneairbornescienceDoesNOT liketo teachbut has toHasinteractedwith a CTD-Rosetteknows 3TaylorSwiftsongsHas beenat sea for>1 weekHas beento theSouthernOceanMovedhousewithin thelast yearFliesdronesHas beenat sea for>1 weekWriteswikipediaarticlesKnowswhat asundog isKnows moreaboutpolarimetrythan owningthe sunglassesHasa dogDoes alot ofoutreachHas beento theArcticOceanPlays amusicalinstrumentCan tell afield workdisasterstoryPrefersto codein pythonPlays amusicalinstrumentHas aGitHubDoes adistancesportDogpersonHas beento aconcert inlast monthWorkswithlidarDoeslakescienceScubadivesHasa catIs anatmosphericscientistDoesnot likepizzaLives >2hoursdrive tothe oceanStarwarsfanFilters alot ofseawaterIshungryright nowHasconsideredbecomingan astronautKnows amagictrickPrefersto codein RWorkswithradarDrove acar >1hour toget hereFlewhere ona planeHas workedin a cleanlab (on landor on a ship)WorkswithcitizenscientistsClimberDid fieldwork inthe lastyearPrefers tocode inMATLABHas useda weatherballoonHas used asun-photometer

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