The Great Thanksgiving Blizzard of 1950

Springfield, Ohio after the snowstorm.

Exactly 67 years ago today, the Great Thanksgiving Blizzard of 1950 began. It was the biggest snowstorm for Columbus, and indeed most of Ohio, during the 40-year period of 1920-1960. That period, especially from the mid-1920s through the mid-1950s, had the lowest rates of cold and snowy winters of any comparable period. The average seasonal snowfall during that period was just 19.1″, a full 9″ below the average the 1980s-2010s have had to date. Still, the period was not without its memorable winters, including 1935-36, 1939-40 and 1947-48. None of those winters, however, had a snow event nearly as big as November 1950.

October 1950 had generally been very warm, ranking historically as the 19th warmest October in Columbus. Highs reached 65 or higher on 21 days of the month. This warmth lasted through early November, and the 80 degrees recorded on November 1st, 1950 remains tied for the warmest November temperature ever recorded. After that, the month seesawed up and down until a strong cold front and rainstorm on the 19th-20th dropped temperatures 25-30 degrees across the state, from the upper 50s-low 60s on the 20th to the low-mid 30s on the 21st. This front would be one of the catalysts for one of Ohio’s greatest winter weather events in its history.

Snow began in Columbus and other parts of Ohio on Thanksgiving, Thursday, November 23rd as a low moved through the Great Lakes and weakened. Behind that system, another cold high pressure was diving south out of Canada.

Thursday, November 23rd 1950 National Map
*Requires a DejaVu plug-in to view.

On Friday the 24th, a low formed on the stalled cold front that had moved through Ohio a few days earlier. Initially forming in southeastern North Carolina, this low would’ve normally gone out to see or moved up the East Coast as a Nor’easter. Instead, the strong, cold high pressure was moving into the Ohio Valley at the same time, and the little low exploded and as it began to move north. The strong push of cold was very evident in Ohio, as temperatures plunged from the upper-30s to upper 40s on Thanksgiving afternoon to single digits and low teens by early Friday morning.

Friday, November 24th, 1950 National Map

The low moved into southern Pennsylvania by the morning of the 25th, and then began to do something few other storms ever do- it began to retrograde toward the west and Ohio, continuing to strengthen as it went. The unusual west movement was caused by a blocking high pressure system parked over Maine.

Saturday, November 25th, 1950 National Map

Light snow that had been ongoing in Ohio on the 24th quickly intensified from east to west across the state as the low moved westward from Central Pennsylvania to Northern Ohio by the end of the day on the 25th. With it arrived winds of 40-60 miles per hour, causing blinding white-outs and drifting.
Saturday the 25th was the height of the storm as the low pressure bottomed out at 978mb, a pressure normally associated with hurricanes. This day was, coincidentally, the famed Ohio State-Michigan rivalry football game, now famously known as the “Snow Bowl” for its terrible weather conditions.

With temperatures on Saturday morning in the single digits, wind chills well below zero and with heavy snow, there was debate about cancelling the game altogether, which was the Big Ten Championship. Ironically, despite the fact that Ohio State would’ve gone on to the Rose Bowl had the game been cancelled (Michigan did not want to reschedule), it was Ohio State’s athletic director who ultimately refused to cancel the game, much to the rest of the staff’s disappointment. Perhaps after the fact, considering Ohio State lost 9-3, that decision was regretted, especially in front of the more than 50,000 die-hard fans that managed to show up for the game.


Columbus would receive 7.5″ at the airport, with eastern suburbs getting up to 10″, just on that Saturday alone.

Due to the blocking high pressure, the storm didn’t budge for days, and it continued through the 26th and 27th before slowly dying out. The last accumulating snowflakes from this system fell on the 29th, 6 days after the snow began.

Sunday, November 26th, 1950 National Map
Monday, November 27th, 1950 National Map
Tuesday, November 28th, 1950 National Map
Wednesday, November 29th, 1950 National Map

All in all, the storm was a record-breaker. Snow totals reached 10″ or more across most of the state except the far northwest and far southwest. In Central Ohio, snow had piled up between 10″-20″, with Columbus officially reporting 15.2″ for the duration of the event. This was the second-heaviest snowstorm in Columbus on record to that time, falling just shy of the 15.3″ that occurred February 17-18, 1910. Both of these storms would be surpassed by the February 14-17, 2003 snowstorm of 15.5″, which itself was surpassed by March 7-8th, 2008’s 20.5″.

Other totals in the state included up to 22″ in Cleveland, 27″ in Marietta, and reports of 44″ in Steubenville in far eastern Ohio. Totals of 25″-30″ were common throughout the eastern 1/3rd of the state. These totals are some of the highest the state has ever seen, coming close to those seen in the eastern Ohio snowstorm of April 1901.

In addition to the snow, record cold temperatures in Columbus of 5 degrees on the 25th (along with a record low maximum of 20) made this one of the greatest early winter events of all time.


Cleveland after the storm.

Thanksgiving Day Historic Weather and Climatology

*Updated through 2016.

Normals *1981-2010
High: 48
Low: 33
Mean: 40.5
Precipitation: 0.11″
Snowfall: 0.1″

Top 10 Coldest Highs
1. 1930: 12
2. 1936: 26
3. 1880, 1903, 1905: 27
4. 1938: 28
5. 1892, 1898: 29
6. 1881: 30
7. 1945, 2002, 2013: 32
8. 1886, 1889, 1890, 1929, 1958: 33
9. 1882, 1885, 1901, 2014: 34
10. 1912, 1947, 1956, 1982, 2000: 35

Top 10 Coldest Lows
1. 1930: 3
2. 1930, 2005: 15
3. 1929, 1984: 16
4. 2000: 17
5. 1880, 1881, 1892, 1894, 1958: 18
6. 1901, 1905, 2002: 19
7. 1898, 1936, 1938, 1950, 1982, 1989, 1996: 20
8. 1911, 1956, 2013: 21
9. 1882, 1886, 1912, 1945: 22
10. 1994, 2008: 23

Top 10 Warmest Highs
1. 1896: 70
2. 2015: 65
3. 1915, 1940: 64
4. 1879, 1908, 1981, 2007, 2012: 63
5. 1966, 1968, 1973, 1979: 62
6. 1918, 1941: 61
7. 1914, 1927, 1983: 60
8. 1933: 59
9. 1899, 1957: 58
10. 1921, 1943, 1990, 2010: 57

Top 10 Warmest Lows
1. 1979: 53
2. 1896: 52
3. 1940: 51
4. 1957: 49
5. 1879: 48
6. 1934, 1966, 2015: 47
7. 1968: 46
8. 1913, 1933, 1978, 1990, 2003, 2016: 43
9. 1899, 1927, 1961: 42
10. 1908, 1951, 1987, 1991, 1998: 41

Top 10 Wettest
1. 2010: 1.76″
2. 1961: 1.58″
3. 1968: 1.22″
4. 1990: 0.71″
5. 1921, 1925: 0.70″
6. 1926: 0.69″
7. 1980: 0.65″
8. 1887: 0.60″
9. 1957: 0.59″
10. 1951: 0.49″

Top 10 Snowiest
1. 1880: 3.2″
2. 1950: 1.1″
3. 1938: 0.8″
4. 1959: 0.7″
5. 1889: 0.4″
6. 1945, 1957: 0.3″
7. 1890, 1954, 2005: 0.2″
8. 1953, 2004: 0.1″
9. Multiple: Trace
10. Multiple: 0


Most Snow on the Ground

1959: 1″
2013: 1″
Trace: Multiple

Young Professionals: A Comparison

**Updated 11/22/2017.

Millennials and Young Professionals are big news these days. Millennials are the largest generation ever in terms of total numbers (exceeding 76 million), and their choices are already having big impacts on everything from housing to the economy, and Young Professionals have long been an important urban demographic. I wanted to look at Columbus and its peers to see where it ranks in terms of attracting the 25-34 age group that include these demographics.

For the comparison, I looked at metro areas of 1.5-2.5 million as well as major Midwest metros and then used their core cities to get the numbers.

Rank of Total Population Aged 25-34

2005_______________________2010___________________2016

1. Chicago: 463,236_______1. Chicago: 510,042________1. Chicago: 532,349
2. San Antonio: 180,981_____2. San Antonio: 200,645____2. San Antonio: 241,783
3. Austin: 137,523_________3. Austin: 162,247_________3. Austin: 214,687
4. San Jose, CA: 133,144___4. Columbus: 147,584______4. Columbus: 180,685
5. Columbus: 131,641______5. San Jose, CA: 142,551___5. San Jose, CA: 165,408
6. Indianapolis: 114,532_____6. Indianapolis: 133,088____6. Charlotte, NC: 149,024
7. Detroit: 110,759_________7. Charlotte, NC: 127,539___7. Indianapolis: 143,328
8. Charlotte, NC: 100,025____8. Portland, OR: 113,210___8. Nashville: 130,593
9. Portland, OR: 90,023_____9. Nashville: 110,882______9. Portland: 127,557
10. Las Vegas: 84,418______10. Milwaukee: 97,359____10. Milwaukee: 101,449
11. Milwaukee: 82,060______11. Detroit: 85,023_______11. Detroit: 101,246
12. Sacramento, CA: 75,497___12. Minneapolis: 81,532__12. Sacramento: 92,883
13. Minneapolis: 74,208___13. Las Vegas: 81,212______13. Minneapolis: 90,022
14. Kansas City, MO: 68,060__14. Sacramento: 78,527__14. Las Vegas: 84,756
15. Virginia Beach: 60,749__15. Kansas City: 73,872____15. Kansas City: 81,532
16. Omaha, NE: 56,248____16. Virginia Beach: 67,614__16. Virginia Beach: 75,365
17. Wichita, KS: 52,426____17. Omaha: 62,396________17. Omaha: 72,055
18. Cleveland: 50,558_____18. St. Louis: 57,627_______18. Orlando: 63,947
19. St. Louis: 48,137______19. Wichita: 56,737________19. Pittsburgh: 62,515
20. Cincinnati: 44,945_____20. Cleveland: 54,428______20. St. Louis: 61,777
21. Toledo: 43,134_______21. Pittsburgh: 51,109______21. Cleveland: 58,773
22. Orlando: 40,846______22. St. Paul: 50,107________22. Wichita: 57,869
23. St. Paul, MN: 39,676__23. Cincinnati: 49,067_______23. St. Paul: 55,306
24. Lincoln, NE: 38,893___24. Orlando: 48,102________24. Cincinnati: 54,754
25. Madison, WI: 38,826___25. Madison: 44,662_______25. Madison: 48,759
26. Pittsburgh: 38,744____26. Lincoln: 42,034_________26. Lincoln: 43,882
27. Grand Rapids: 35,287__27. Toledo: 41,580________27: Toledo: 42,888
28. Des Moines: 32,640__28. Fort Wayne: 35,193______28. Grand Rapids: 39,829
29. Fort Wayne, IN: 31,738__29. Providence: 31,044____29. Fort Wayne: 37,372
30. Akron: 30,436_______30. Grand Rapids: 30,963____30. Des Moines: 34,961
31. Providence, RI: 29,307__31. Des Moines: 30,376____31. Providence: 30,630
32. Dayton: 18,591_______32. Akron: 27,446_________32. Akron: 29,786
33. Youngstown: 8,505____33. Dayton: 20,278________33. Dayton: 22,930
34. Nashville, TN: N/A___34. Youngtown: 8,484_______34. Youngstown: 7,621

So Columbus ranks highly among total population in the 25-34 age group. But what about growth?

Total Growth Rank in 25-34 Population 2005-2016

1. Austin, TX: 77,164
2. Chicago: 69,113
3. San Antonio, TX: 60,802
4. Columbus: 49,044
5. Charlotte, NC: 48,999
6. Portland, OR: 37,534
7. San Jose, CA: 32,264
8. Indianapolis, IN: 28,796
9. Pittsburgh, PA: 23,771
10. Orlando, FL: 23,101
11. Milwaukee, WI: 19,389
12. Sacramento, CA: 17,386
13. Minneapolis, MN: 15,814
14. Omaha, NE: 15,807
15. St. Paul, MN: 15,630
16. Virginia Beach, VA: 14,616
17. St. Louis, MO: 13,642
18. Kansas City, MO: 13,472
19. Madison, WI: 9,933
20. Cincinnati: 9,809
21. Cleveland: 8,215
22. Fort Wayne, IN: 5,634
23. Wichita, KS: 5,443
24. Lincoln, NE: 4,989
25. Grand Rapids, MI: 4,542
26. Dayton: 4,339
27. Des Moines, IA: 2,321
28. Providence, RI: 1,323
29. Las Vegas, NV: 338
30. Toledo: -246
31. Akron: -650
32. Youngstown: -884
33. Detroit, MI: -9,513
34. Nashville: N/A

Again, Columbus ranks near the top during this period. What about more recently, since 2010?

Total Growth Rank of 25-34 Population 2010-2016

1. Austin: 52,440
2. San Antonio: 41,138
3. Columbus: 33,101
4. San Jose: 22,857
5. Chicago: 22,307
6. Charlotte: 21,485
7. Nashville: 19,711
8. Detroit: 16,223
9. Orlando: 15,845
10. Sacramento: 14,356
11. Portland: 14,347
12. Pittsburgh: 11,406
13. Indianapolis: 10,240
14. Omaha: 9,659
15. Grand Rapids: 8,866
16. Minneapolis: 8,490
17. Virginia Beach: 7,751
18. Kansas City: 7,660
19. Cincinnati: 5,687
20. St. Paul: 5,199
21. Des Moines: 4,585
22. Cleveland: 4,345
23. St. Louis: 4,152
24. Madison: 4,097
25. Milwaukee: 4,090
26. Las Vegas: 3,544
27. Dayton: 2,652
28. Akron: 2,340
29. Fort Wayne: 2,179
30. Lincoln: 1,848
31. Toledo: 1,308
32. Wichita: 1,132
33. Providence: -414
34. Youngstown: -863

So Columbus is also doing well since 2010 and attracts significantly more people in the 25-34 age group than cities often cited for this very metric.

Finally, now that we know the totals and the growth, what is the % of total city population that the 25-34 age group makes up?

25-34 % of Total City Population 2016

1. Orlando: 23.1%
2. Austin: 22.6%
3. Minneapolis: 21.8%
4. Columbus: 20.9%
5. Pittsburgh: 20.6%
6. Grand Rapids: 20.3%
7. Portland: 19.9%
8. Nashville: 19.8%
9. St. Louis: 19.8%
10. Chicago: 19.7%
11. Madison: 19.3%
12. Sacramento: 18.8%
13. Cincinnati: 18.3%
14. St. Paul: 18.3%
15. Charlotte: 17.7%
16. Providence: 17.1%
17. Milwaukee: 17.0%
18. Kansas City: 16.9%
19. Indianapolis: 16.8%
20. Virginia Beach: 16.7%
21. Des Moines: 16.2%
22. San Antonio: 16.2%
23. Omaha: 16.1%
24. San Jose: 16.1%
25. Lincoln: 15.7%
26. Toledo: 15.4%
27. Cleveland: 15.2%
28. Akron: 15.1%
29. Detroit: 15.0%
30. Wichita: 14.8%
31. Fort Wayne: 14.3%
32. Las Vegas: 13.4%
33. Youngstown: 11.9%
34. Dayton: 8.2%

Columbus has an existing large population of the 25-34 age demographic, and looks to be one of the strongest performers into the near future.
Some would ask why that would be considering that Columbus transit is woefully lacking and has a reputation (very undeservedly, in my opinion) of being suburban- characteristics that Millennials/YPers supposedly almost universally reject. Perhaps the bottom line is that economics trump all other desires. Cost of living and employment tend to be higher up the list than rail lines, and Columbus has both a strong economy and relatively low COL. Whatever the case may be, Columbus seems to be doing something right.

Historic Halloween Weather

1981-2010 Halloween Averages
High: 61
Low: 41
Mean: 51
Precipitation: 0.09″
Snowfall: 0.0″

Top 20 Warmest Halloween Highs
1. 1950: 83
2. 1974: 80
3. 1900: 79
4. 1927, 1933: 78
5. 1979, 2003: 75
6. 1882, 1901, 1982, 1999: 74
7. 1909, 1990: 73
8. 1888, 1935, 1944, 1987: 72
9. 1915, 1971: 71
10. 1919: 70
11. 1891, 1986, 2001, 2008: 69
12. 1929, 1956, 1978, 1981, 1985, 2005, 2007: 68
13. 1903, 1943, 1946, 1952, 1991, 2013: 67
14. 1902, 1916, 1953, 1965, 1984: 66
15. 1942, 1958, 1961, 1968, 1969, 2009: 65
16. 1896, 1897, 1912, 1921, 1922, 1940, 1945, 1964, 1997, 2004: 64
17. 1914, 1941, 1970, 2000, 2006: 63
18. 1886, 1924, 1934, 1959, 1977, 1983, 1998: 62
19. 1892, 1938, 1989, 1995: 61
20. 1963, 1966, 1994: 60

Top 20 Coldest Halloween Highs
1. 1906: 38
2. 1993: 39
4. 1878, 1895: 40
5. 1913, 1923, 1954: 41
6. 1885, 1917, 2012: 42
7. 1890: 43
8. 1908, 1925, 1926: 44
9. 1898, 1905: 45
10. 1930, 1976: 46
11. 1879, 1931, 2002: 47
12. 1894, 1918, 1939: 48
13. 1955, 1962, 1996, 2014: 49
14. 1880, 1972: 50
15. 1973, 2010, 2011: 52
16. 1907, 1951, 1988: 53
17. 1887, 1893, 1932, 2015: 54
18. 1883, 1928, 1949, 1975: 55
19. 1899, 1967: 56
20. 1884, 1911, 1937, 1957, 1980, 1992: 57

Top 20 Warmest Halloween Lows
1. 1919: 61
2. 1882: 60
3. 2003: 59
4. 1927, 1929: 58
5. 1900, 1956, 2013: 57
6. 1921, 1941, 1982: 56
7. 1950: 55
8. 1959, 1979: 54
9. 1971: 53
10. 1881, 1891, 1933, 1946, 1974, 1991: 52
11. 1901, 1984, 1998: 51
12. 1947: 50
13. 1961, 2001: 49
14. 1935, 1948, 1960, 1967, 1985, 1995, 1999: 48
15. 1889, 1896, 1909, 1943, 1977: 47
16. 1924, 1945, 2004, 2016: 46
17. 1899, 1911, 1916: 45
18. 1903, 1940, 2015: 44
19. 1965, 1970, 1973, 1981, 1989, 1990, 1992, 1997, 2009: 43
20. 1888, 1942, 1957, 1994, 2006: 42

Top 20 Coldest Halloween Lows
1. 1887: 20
2. 1962, 1988: 25
3. 1923: 27
4. 1908, 1925: 28
5. 1885, 1893, 1913, 1917, 1953, 1975: 29
6. 1904, 1906: 30
7. 1878, 1938, 1954, 1968: 31
8. 1928, 1934, 1949, 1958, 1964, 1976, 1980, 2000: 32
9. 1879, 1926, 1930: 33
10. 1890, 1936, 1951, 1966, 1969, 1993, 1996, 2002, 2008, 2010: 34
11. 1892, 1920: 35
12. 1894, 1895, 1932, 1955, 1978: 36
13. 1910, 1983: 37
14. 1886, 1898, 1914, 1939, 1944, 1963, 2007, 2012, 2014: 38
15. 1884, 1905, 1918, 1937, 2005, 2011: 39
16. 1880, 1883, 1907, 1952, 1972, 1986, 1987: 40
17. 1897, 1902, 1912, 1915, 1922, 1931: 41
18. 1888, 1942, 1957, 1994, 2006: 42
19. 1965, 1970, 1973, 1981, 1989, 1990, 1992, 1997, 2009: 43
20. 1903, 1940, 2015: 44

Top 20 Wettest Halloweens
1. 1932: 1.44″
2. 2009: 1.21″
3. 2013: 0.98″
4. 1941: 0.97″
5. 1919: 0.91″
6. 1942: 0.51″
7. 1960: 0.45″
8. 1905, 1973: 0.43″
9. 2006: 0.36″
10. 1989: 0.34″
11. 1976: 0.32″
12. 1993: 0.31″
13. 1972: 0.29″
14. 1994: 0.26″
15. 1895: 0.23″
16. 1959: 0.20″
17. 1948: 0.18″
18. 1889: 0.17″
19. 1921, 1951: 0.15″
20. 1963, 1967, 2012, 2014: 0.11″

Snowiest Halloweens
1. 1993: 1.0″
2. 1954: 0.2″
3. 1906, 1917, 1926, 1930, 1951, 2012: Trace

Greatest Snow Depth
1. 1954: Trace