June’s Missed Opportunity of the Month




Columbus, as recent estimates show, is clearly becoming a real player on the national stage in terms of its rapid growth and increasing name recognition. There’s a lot to be proud of for a city located in what many people think is just the Rust Belt. But as with every city, Columbus doesn’t get it all right all the time. A while back, I wrote how Columbus could sometimes be a city of missed opportunities when it came to development, and that remains true. For every great project in the Short North, there’s an equally terrible development going up somewhere else. In what I want to be a semi-regular series, I’m going to highlight some projects that simply miss the boat in terms of good urban development. Some are merely not reaching their potential, and then some, like June’s missed opportunity of the month, is an out of left field example that seems to be trying so hard, only to fail equally so.

That project is the redevelopment of the University City strip mall off of Olentangy River Road.

Aerial photo.

As you can see from the aerial, the site is your typical strip mall. Built in 1961 when such developments were seen as community shopping destinations rather than the dying suburban sprawl they have become, University City is completely nondescript and looks no different than hundreds of others dotting the landscape. Anchored by a Kroger, the strip mall held other stereotypical establishments- a salon, bars, a Chinese restaurant, etc. A handful of out lots contain a McDonald’s, gas station and a bank.


Most of the site, of course, is taken up by enormous amounts of surface parking, most of which sits empty more often than not.

Olentangy River Road is not exactly an urban street. Most of it is lined with hotels, restaurants and offices, all set well back from the road and in a generally unfavorable configuration to encourage walkability. So when it was announced in June of last year that the strip mall would be redeveloped, hope for something substantially different seemed possible. The initial renderings showed a 6-story mixed-use building on the site instead of the strip mall.

MUCH better, right? Of course, saying it’s much better is a low bar compared to the current situation, but a 6-story, mixed-use project is truly urban, and one of the first of its kind on Olentangy River Road. So why, one might ask, is this a missed opportunity?
To answer that, we have to look at the proposed layout of the entire site.

Comparing the proposed layout to the current one is a little confusing, because they look extremely similar. It seems that the 6-story project will only replace the current strip center, but most of the parking and all of the out lots will remain intact. It’s a Frankenstein’s monster of suburban and urban elements that just looks really weird. There is no interaction with any of the nearby roads, and not even a resident pathway from the main building to the multi-use path that was built a few years ago along Olentangy. It’s all still catering to cars.
In the most recent rendering of the main building, seen below, there appears to be only 1 patio space for what is clearly a very large project. The view for customers from there, of course, is still just the parking lot, with its noise, pollution and lack of any shade. In fact that’s basically the view out of every window in the building- parking lots.

I suppose that some surface lots and outbuildings could eventually be redeveloped at some point, but as it stands now, there’s a lot to be desired. The main building is decent, but the overall layout and connections are terrible and it makes the whole project just look like a much larger version of the strip mall that’s already there. Maybe that’s a harsh assessment, but I don’t think it’s an unfair one. Casto, the developer, basically invented the strip mall, so they’re clearly playing to their strengths here. They’ve done some really good projects at times, like the renovation of the Julian building on South Front Street in Downtown, and I applaud the effort to go more urban in this location, but I think so much could’ve been done better in this case. No doubt that this development will have no trouble finding tenants to rent the apartments, just due to the lack of housing anywhere in the core, but I question just what this development offers that better ones don’t.

In the end, it is a good example of how Columbus needs more true urban developers that are comfortable and willing to push the envelope on this style of development. Trying to have it both ways, where suburbia reigns in an urban location, gets us nowhere.




2017 Ohio City Population Estimates




city population estimates

So once again, 2017 Ohio city population estimates came out today from the Census. As has been the case for a long time now, Columbus is rocketing upward at record pace. The 2016 comparison numbers have been adjusted by the Census for the 2017 update.

First, let’s take a look at the top 25 largest cities in Ohio on July 1, 2017.
Census 2010—————————-July 1, 2016——————-July 1, 2017
1. Columbus: 787,033——–1. Columbus: 863,741———–1. Columbus: 879,170
2. Cleveland: 396,815———2. Cleveland: 387,451———-2. Cleveland: 385,525
3. Cincinnati: 296,943———3. Cincinnati: 299,127———-3. Cincinnati: 301,301
4. Toledo: 287,208————-4. Toledo: 278,06—————4. Toledo: 276,491
5. Akron: 199,110————–5. Akron: 197,711—————5. Akron: 197,846
6. Dayton: 141,527————6. Dayton: 140,743————–6. Dayton: 140,371
7. Parma: 81,601————–7. Parma: 79,591—————–7. Parma: 79,167
8. Canton: 73,007————-8. Canton: 71,294—————-8. Canton: 70,909
9. Youngstown: 66,982——9. Youngstown: 64,360———9. Youngstown: 64,604
10. Lorain: 64,097————10. Lorain: 63,700—————-10. Lorain: 63,841
11. Hamilton: 62,477———11. Hamilton: 62,157————11. Hamilton: 62,092
12. Springfield: 60,608——-12. Springfield: 58,902———12. Springfield: 59,208
13. Kettering: 56,163———13. Kettering: 55,218————13. Kettering: 55,175
14. Elyria: 54,533————-14. Elyria: 53,880—————–14. Elyria: 53,883
15. Lakewood: 52,131——-15. Lakewood: 50,500———-15. Lakewood: 50,249
16. Cuyahoga Falls: 49,652–16. Cuyahoga Falls: 49,197–16. Newark: 49,423
17. Euclid: 48,920————-17. Newark: 48,899———-17. Cuyahoga Falls: 49,247
18. Middletown: 48,694——18. Middletown: 48,819——–18. Middletown: 48,823
19. Mansfield: 47,821——–19. Euclid: 47,464—————19. Dublin: 47,619
20. Newark: 47,573———–20. Mentor: 46,823————-20. Euclid: 47,201
21. Mentor: 47,159————21. Mansfield: 46,671———-21. Mentor: 47,121
22. Cleveland Heights: 46,121–22. Beavercreek: 46,393–22. Beavercreek: 46,948
23. Beavercreek: 45,193—–23. Dublin: 45,673————-23. Mansfield: 46,160
24. Strongsville: 44.750—–24. Cleveland Heights: 44,805–24. Strongsville: 44,744
25. Fairfield: 42,510———25. Strongsville: 44,713———25. Cleveland Heights: 44,562

So Columbus easily maintained #1, and Dublin and Newark are rapidly climbing the list.

Here are all of the Columbus Metro’s cities, towns and villages on July 1, 2017, and the total change from July 1, 2016.
1. Columbus: 879,170 +15,429
2. Newark: 49,423 +534
3. Dublin: 47,619 +1,937
4. Grove City: 41,022 +1,128
5. Lancaster: 40,280 +431
6. Westerville: 39,737 +671
7. Delaware: 39,267 +506
8. Reynoldsburg: 37,847 +345
9. Hilliard: 35,939 +938
10. Upper Arlington: 35,337 +217
11. Gahanna: 35,297 +241
12. Marysville: 23,912 +462
13. Pickerington: 20,402 +350
14. Whitehall: 18,913 +89
15. Pataskala: 15,566 +147
16. Worthington: 14,646 +71
17. Circleville: 13,930 +80
18. Bexley: 13,786 +48
19. Powell: 13,204 +400
20. New Albany: 10,718 +301
21. Heath: 10,713 +100
22. London: 10,138 +143
23. Canal Winchester: 8,294 +349
24. Grandview Heights: 7,778 +116
25. Logan: 7,069 +25
26. Granville: 5,773 +11
27. Groveport: 5,621 +26
28. Sunbury: 5,293 +57
29. Johnstown: 5,002 +43
30. Obetz: 4,967 +99
31. New Lexington: 4,704 -12
32. Plain City: 4,379 +32
33. West Jefferson: 4,355 +59
34. Ashville: 4,147 +29
35. Mount Gilead: 3,655 +1
36. Baltimore: 2,989 +15
37. Buckeye Lake: 2,816 +18
38. Crooksville: 2,491 -6
39. Hebron: 2,435 +23
40. Richwood: 2,372 +56
41. Utica: 2,211 +17
42. Cardington: 2,048 +2
43. South Bloomfield: 1,972 +19
44. Roseville: 1,839 -4
45. Mount Sterling: 1,767 +10
46. Commercial Point: 1,629 +13
47. Lithopolis: 1,573 +128
48. Ashley: 1,537 +26
49. Somerset: 1,462 -1
50. Bremen: 1,441 +6
51. Minerva Park: 1,321 +6
52. Hanover: 1,178 +15
53. Williamsport: 1,065 +6
54. Millersport: 1,055 +7
55. Urbancrest: 1,001 +6
56. Thornville: 999 +5
57. Pleasantville: 964 +3
58. Milford Center: 860 +20
59. New Holland: 840 +5
60. Junction City: 808 -2
61. Shawnee Hills: 787 +14
62. Amanda: 747 +4
63. Ostrander: 713 +13
64. New Straitsville: 711 -1
65. Marble Cliff: 683 +10
66. Galena: 682 +1
67. Shawnee: 643 -1
68. Valleyview: 638 +1
69. Thurston: 609 +4
70. Corning: 571 -1
71. Butchel: 568 +5
72. Stoutsville: 567 +3
73. Riverlea: 566 +2
74. Carroll: 560 +33
75. Kirkersville: 542 +3
76. Alexandria: 534 +3
77. Laurelville: 511 +2
78. Murray City: 441 +1
79. Edison: 438 +0
80. Sugar Grove: 426 +0
81. Hartford: 404 +2
82. St. Louisville: 380 +4
83. South Solon: 357 -1
84. Marengo: 338 -1
85. Harrisburg: 335 +4
86. Midway: 326 +1
87. Rushville: 310 +2
88. Magnetic Springs: 285 +8
89. Tarlton: 282 +1
90. Orient: 278 +1
91. Fulton: 258 +0
92. Lockbourne: 246 +0
93. Darbyville: 234 +1
94. Unionville Center: 232 -1
95. Chesterville: 227 +0
96. Gratiot: 222 +1
97. Glenford: 172 +0
98. Sparta: 158 -3
99. Hemlock: 152 +0
100. West Rushville: 135 +1
101. Brice: 119 +1
102. Rendville: 36 +0

Some milestones include Grove City and Lancaster passing 40,000 for the first time and Johnstown passing the 5,000 mark. 11 places lost population, 8 stayed the same and 83 gained population. The growing portions of the Columbus metro continue to encompass the vast majority of incorporated places.

Nationally, here were the top 20 fastest-growing cities by numerical change between July 1, 2016 and July 1, 2017
1. San Antonio, Texas: +24,208
2. Phoenix, Arizona: 24,036
3. Dallas, Texas: +18,935
4. Fort Worth, Texas: +18,664
5. Los Angeles: 18,643
6. Seattle, Washington: +17,490
7. Charlotte, North Carolina: +15,551
8. Columbus: +15,429
9. Frisco, Texas: +13,470
10. Atlanta, Georgia: +13,323
11. San Diego, California: +12,834
12. Austin, Texas: +12,515
13. Jacksonville, Florida: +11,169
14. Irvine, California: +11,068
15. Henderson, Nevada: +10,534
16. Las Vegas, Nevada: 9,966
17. Denver, Colorado: 9,844
18. Washington, DC: 9,636
19. Tampa, Florida: 9,383
20. Mesa, Arizona: 9,025

Columbus may in fact be an official boomtown now.



Suburban vs. Urban Growth in US Metros




suburban vs urban growth

Now that we have the full set of 2017 population estimates, I wanted to examine a popular claim a little more closely. The claim is that suburban growth far exceeds that of core cities/counties, and it’s often repeated in media throughout the country. One of the things that always bothered me about this was the constant use of basing this claim largely on % change. This has a major flaw, one that I will go into more below.

For this little study on suburban vs urban growth, I will look at the top 50 largest metro areas.

First, let’s look at the total change in the whole metro area, the core county and the core city between the 2010 Census and July 1, 2017. They will be ranked here by total metro change.
1. Dallas, TX: +973,431
2. Houston, TX: +971,941
3. New York, NY: +754,396
4. Atlanta, GA: +597,993
5. Miami, FL: +592,525
6. Washington, DC: +580,228
7. Phoenix, AZ: +544,141
8. Los Angeles, CA: +524,946
9. Seattle, WA: +427,240
10. Austin, TX: +399,507
11. San Francisco, Ca: +391,784
12. Orlando, FL: +375,432
13. Riverside, CA: +355,705
14. Denver, CO: +344,635
15. San Antonio, TX: +331,458
16. Charlotte, NC: +308,313
17. Tampa, FL: +307,930
18. Boston, MA: +283,935
19. Las Vegas, NV: +252,810
20. Minneapolis, MN: +251,760
21. San Diego, CA: +242,343
22. Nashville, TN: +232,162
23. Portland, OR: +227,167
24. Raleigh, NC: +204,590
25. Columbus: +176,724
26. Sacramento, CA: +175,740
27. San Jose, CA: +161,523
28. Jacksonville, FL: +159,382
29. Indianapolis, IN: +140,524
30. Oklahoma City, OK: +130,746
31. Philadelphia, PA: +130,427
32. Kansas City, MO: +119,574
33. Salt Lake City, UT: +115,297
34. Baltimore, MD: +97,572
35. Richmond, VA: +86,117
36. New Orleans, LA: +85,903
37. Chicago: +71,499
38. Cincinnati: +64,396
39. Louisville, KY: +58,247
40. Virginia Beach, VA: +48,429
41. Memphis, TN: +23,433
42. Birmingham, AL: +21,751
43. Milwaukee, WI: +20,282
44. Providence, RI: +19,912
45. St. Louis, MO: +19,575
46. Detroit: +16,685
47. Buffalo, NY: +1,239
48. Hartford, CT: -2,139
49. Cleveland: -18,427
50. Pittsburgh, PA: -22,924

Now that we have the total growth, let’s break it down a bit more.

How much of the total metro change occurred in the core county of each metro? This will be ranked by the highest to lowest % occurring in the core county.

Core County Change—————-Core County % of Total Metro
1. Las Vegas: +252,810———————-100.00%
2. San Diego: +242,343———————-100.00%
3. San Jose: +161,523**———————100.00%
4. Buffalo: +6,488——————————100.00%
5. Salt Lake City: +105,994——————91.93%
6. Phoenix: +489,916————————–90.03%
7. Raleigh: +171,210————————–83.68%
8. San Antonio: +243,805——————–73.56%
9. Columbus: +128,567———————–72.75%
10. Los Angeles: +344,902——————65.70%
11. Sacramento: +111,827——————63.63%
12. Seattle: +257,400————————-60.25%
13. New York: +447,565*——————–59.33%
14. Tampa: +179,340————————-58.24%
15. Houston: +560,521———————–57.67%
16. New Orleans: +49,463——————-57.58%
17. Jacksonville: +88,902——————–55.78%
18. Riverside: +198,100———————-55.69%
19. Providence: +10,870———————54.59%
20. Orlando: +203,019————————54.08%
21. Oklahoma City: +69,325—————-53.02%
22. Louisville: +30,052———————–51.59%
23. Charlotte: +157,209———————50.99%
24. Austin: +202,432————————-50.67%
25. Miami: +255,361————————-43.10%
26. Memphis: +9,317————————39.76%
27. Minneapolis: +99,599——————-39.56%
28. Indianapolis: +46,689——————33.22%
29. Philadelphia: +41,866——————32.10%
30. Portland: +72,221———————–31.79%
31. Denver: +104,463**———————30.31%
32. Nashville: +64,663———————-27.85%
33. Boston: +75,916————————-26.74%
34. Richmond: +22,818**——————26.50%
35. Virginia Beach: +12,441**————25.69%
36. Dallas: +250,009————————25.68%
37. Chicago: +16,588———————–23.20%
38. Milwaukee: +4,350———————21.45%
39. Kansas City: +24,737—————–20.69%
40. Atlanta: +120,843———————-20.21%
41. San Francisco: +79,128**————20.20%
42. Cincinnati: +11,448——————–17.78%
43. Washington, DC: +92,249**———15.90%
44. Birmingham: +731———————-3.36%
45. Hartford: +1,374————————-0.0%
46. Baltimore: -9,313**———————-0.0%
47. St. Louis: -10,668**———————0.0%
48. Detroit: -66,968————————–0.0%
49. Pittsburgh: -300———————– -1.31%
50. Cleveland: -31,608——————- -100.00%

*New York includes all 5 main boroughs, so it is different than core county, but still represents the urban center of the metro area.
**Core County and City are consolidated, or city exists as separate entity.

Going down even further, let’s compare the core city to the total metro, again ranked by %.

Core City Change————————Core City % of Total Metro
1. New York: +447,565————————-59.33%
2. New Orleans: +49,463———————–57.58%
3. San Antonio: +184,539———————-55.67%
4. San Jose: +89,375—————————55.33%
5. Columbus: +92,137————————–52.14%
6. Oklahoma City: +63,649——————–48.68%
7. San Diego: +112,114————————46.26%
8. Jacksonville: +70,278———————–44.09%
9. Philadelphia: +54,857———————–42.06%
10. Charlotte: +127,611————————41.39%
11. Louisville: +24,012————————-41.22%
12. Austin: +160,325—————————40.13%
13. Los Angeles: +207,138——————-39.46%
14. Las Vegas: +64,468———————–36.68%
15. Phoenix: +180,446————————-33.16%
16. Raleigh: +65,098—————————31.82%
17. Denver: +104,463————————–30.31%
18. Indianapolis: +42,557———————30.28%
19. Chicago: +20,852————————–29.16%
20. Portland: +64,029————————–28.19%
21. Nashville: +64,562————————-27.81%
22. Seattle: +116,085————————–27.17%
23. Richmond: +22,818**———————26.50%
24. Virginia Beach: +12,441**—————25.69%
25. Kansas City: +29,156———————24.38%
26. Boston: +67,500—————————23.77%
27. Memphis: +5,347————————–22.82%
28. Houston: +212,454————————21.86%
29. San Francisco**: +79,128—————20.20%
30. Sacramento: +35,413———————20.15%
31. Minneapolis: +41,412———————16.45%
32. Tampa: +49,721—————————-16.15%
33. Washington, DC: +92,249**————-15.90%
34. Dallas: +143,259—————————14.72%
35. Salt Lake City: +14,104——————-12.23%
36. Providence: +2,351————————11.81%
37. Orlando: +41,957—————————11.18%
38. Atlanta: +66,287—————————-11.08%
39. Miami: +54,122——————————9.13%
40. Cincinnati: +4,356————————–6.76%
41. Riverside: +23,857————————-6.71%
42. Milwaukee: +518—————————2.55%
43. Birmingham: -1,527———————–0.0%
44. Buffalo: -5,218——————————0.0%
45. Baltimore: -9,313**————————0.0%
46. St. Louis: -10,668**———————–0.0%
47. Detroit: -40,673—————————-0.0%
48. Pittsburgh: -3,297———————– -14.38%
49. Cleveland: -10,889——————— -59.09%
50. Hartford: -1,375————————- -64.28%

*Again, I used the 5 boroughs of New York here, so the numbers don’t change.
**See above.

Finally, because core counties and cities can be absolutely huge, like in Phoenix, I wanted to take see the ratio of people moving vs. the area size. To do this, I divided the growth by the land area of each core county and city.

So basically, how many people moved there per each square mile.

Core County Ratio——————————-Core City Ratio
1. San Francisco: 1,687.52————————-1,687.52
2. Washington, DC: 1,511.04———————-1,511.04
3. New York: 1,475.51——————————-1,475.51
4. Boston: 1,308.90———————————–1,394.05
5. Denver: 681.30————————————–681.30
6. Richmond: 379.67———————————-379.67
7. Houston: 329.14————————————354.33
8. Philadelphia: 312.43——————————-408.83
9. Charlotte: 300.02———————————–428.66
10. New Orleans: 291.95—————————-291.95
11. Dallas: 286.38————————————-420.73
12. Columbus: 241.67——————————-424.26
13. Atlanta: 229.30———————————–497.65
14. Orlando: 224.83———————————-398.75
15. Raleigh: 205.04———————————-455.87
16. Austin: 204.48————————————538.18
17. San Antonio: 196.62—————————-400.36
18. Minneapolis: 179.78—————————–754.32
19. Tampa: 175.82————————————438.38
20. Portland: 167.57———————————-481.42
21. Salt Lake City: 142.85—————————129.28
22. Miami: 134.54————————————-1,503.81
23. Nashville: 128.30———————————128.01
24. San Jose: 125.21———————————503.49
25. Seattle: 121.64————————————1,384.11
26. Indianapolis: 117.81——————————117.72
27. Jacksonville: 116.67——————————94.02
28. Sacramento: 115.88——————————361.65
29. Oklahoma City: 97.78—————————-105.89
30. Los Angeles: 84.99——————————-441.90
31. Louisville: 79.08———————————–63.11
32. San Diego: 57.84———————————344.76
33. Phoenix: 53.25————————————348.59
34. Virginia Beach: 49.96—————————-49.96
35. Kansas City: 40.96——————————-92.57
36. Las Vegas: 32.04———————————474.73
37. Cincinnati: 28.20———————————-55.89
38. Riverside: 27.49———————————–293.70
39. Providence: 26.51——————————–127.08
40. Milwaukee: 18.05———————————5.39
41. Chicago: 17.5————————————–91.72
42. Memphis: 12.21———————————–16.97
43. Buffalo: 6.22————————————– -128.52
44. Harford: 1.87————————————- -79.02
45. Birmingham: 0.66——————————- -10.46
46. Pittsburgh: -0.41——————————— -59.53
47. Cleveland: -69.16——————————- -140.14
48. Detroit: -109.42———————————- -293.14
49. Baltimore: -115.12—————————— -115.12
50. St. Louis: -172.34——————————- -172.34

So what’s all this mean? Columbus performs particularly well here. Franklin County attracts a high percentage of the total metro population, and Columbus itself is one of only 5 cities with more than 50% of the metro growth entering the city limits. Even accounting for area size, Columbus does fairly well. This suggests that urban growth there is stronger than in most cities.



Random Columbus Photo 5




Photo Location: Broad and High
Photo Date: Sometime in 1849
Photo History: Random Columbus photo 5 is one of the earliest ever known to have been taken in Columbus, and shows a group of bystanders looking at several people on horseback. The year this was taken, 1849, is significant in that it references the events taking place. 1849, of course, was the year that gold was discovered in California. The men on horseback are 49-ers, getting ready to depart Columbus to join the great California Gold Rush, and the crowd was gathered to see them off.

Random Columbus photo 5

Click on the image for a better look.

Unfortunately, not much else is known about the photo, who the people were, or in what direction the photo was even taken.

Winter 2017-2018 Review




Winter 2017-2018 Review Columbus, Ohio

Wind and heavy snow on the evening of January 12, 2018.

The Winter 2017-2018 Review shows the season featured some wild swings, from a very cold late December-early January to one of the warmest Februaries of all time. Let’s take a closer look at this volatile season, specifically December to February.

Temperature and snowfall ranking data goes back to the winter of 1878-1879. Snow depth ranking data goes back to 1940.

December-February Only
Average High: 40.2 29th Warmest
Average Low: 24.2 42nd Warmest
Mean: 32.2 36th Warmest
Precipitation: 9.40″ 33rd Wettest
Snowfall: 24.6″ 32nd Snowiest
Average Daily Snow Depth: 0.7″ 8th Lowest
32 or Below Highs: 29 21st Most
32 or Below Lows: 70 18th Fewest
Measurable Precipitation Days: 40
Measurable Snowfall Days: 20
Deepest Snow Depth: 5″ on January 16th and 17th
Days with 1″+ Snow Depth: 26 19th Most

Entire Cold Season: October-April
Average High: 49.6 29th Warmest
Average Low: 32.0 36th Coldest
Mean: 40.8 30th Warmest
Precipitation: 25.83″ 13th Wettest
Snowfall: 30.7″ 34th Snowiest
Average Snow Depth: 0.3″ 4th Lowest
32 or Below Highs: 29 19th Fewest
32 or Below Lows: 119 14th Most
Measurable Precipitation Days: 87 18th Most
Measurable Snowfall Days: 34 11th Most
Deepest Snow Depth: 5″ on January 16th and 17th
Days with 1″+ Snow Depth: 31 20th Most

Average High By Month
October 2017: 68.5 21st Warmest
November 2017: 52.5 33rd Warmest
December 2017: 38.6 36th Coldest
January 2018: 35.4 39th Coldest
February 2018: 47.3 7th Warmest
March 2018: 47.5 36th Coldest
April 2018: 58.0 14th Coldest

Average Low By Month
October 2017: 48.8 15th Warmest
November 2017: 34.8 38th Warmest
December 2017: 23.7 33rd Coldest
January 2018: 19.3 39th Coldest
February 2018: 30.3 9th Warmest
March 2018: 29.6 33rd Coldest
April 2018: 37.5 9th Coldest

Mean By Month
October 2017: 58.6 16th Warmest
November 2017: 43.6 32nd Warmest
December 2017: 31.2 37th Coldest
January 2018: 27.3 39th Coldest
February 2018: 38.8 7th Warmest
March 2018: 38.5 36th Coldest
April 2018: 47.7 12th Coldest

Precipitation By Month
October 2017: 3.57″ 28th Wettest
November 2017: 4.67″ 15th Wettest
December 2017: 1.76″ 28th Driest
January 2018: 2.39″ 64th Wettest
February 2018: 5.25″ 8th Wettest
March 2018: 2.96″ 57th Driest
April 2018: 5.23″ 15th Wettest

Snowfall By Month
October 2017: Trace 2nd Least Snowy
November 2017: Trace 2nd Least Snowy
December 2017: 8.1″ 23rd Snowiest
January 2018: 10.5″ 38th Snowiest
February 2018: 6.0″ 45th Snowiest
March 2018: 3.2″ 48th Least Snowy
April 2018: 2.9″ 8th Snowiest

Average Snow Depth By Month
October 2017: 0″ 1st Lowest
November 2017: 0″ 1st Lowest
December 2017: 0.3″ 4th Lowest
January 2018: 1.4″ 15th Lowest
February 2018: 0.4″ 5th Lowest
March 2018: 0.1″ 2nd Lowest
April 2018: 0.1″ 2nd Lowest



Maximum High By Month
October 2017: 86 on the 4th
November 2017: 73 on the 5th
December 2017: 60 on the 4th
January 2018: 60 on the 11th and 22nd
February 2018: 77 on the 20th
March 2018: 61 on the 19th and 29th
April 2018: 82 on the 13th

Record Highs
-The 77 on February 20th was a record for the date, beating the old record of 68 set in 1891 and 2016.

Minimum High By Month
October 2017: 43 on the 28th
November 2017: 35 on the 10th
December 2017: 17 on the 27th
January 2018: 10 on the 2nd
February 2018: 22 on the 2nd
March 2018: 33 on the 8th
April 2018: 37 on the 17th

Minimum High Records
-The 10 on January 2nd was a record for the date, beating the old record of 11 set in 1928.
-The 37 on April 17th was a record for the date, beating the old record of 39 set in 1907.

Maximum Low By Month
October 2017: 66 on the 7th
November 2017: 60 on the 5th
December 2017: 47 on the 22nd
January 2018: 52 on the 11th
February 2018: 60 on the 20th
March 2018: 51 on the 28th
April 2018: 63 on the 13th

Record Maximum Lows
-The 47 on December 22nd tied the record set in 2015, and ties for the warmest December low on record.
-The 55 on February 15th was a record for the date, beating the old record of 53 set in 1954.
-The 60 on February 20th was a record for the date, beating the old record of 49 set in 1930.
-The 63 on April 13th was a record for the date, beating the old record of 61 set in 1916.

Minimum Low By Month
October 2017: 31 on the 26th
November 2017: 21 on the 11th
December 2017: 2 on the 31st
January 2018: -4 on the 2nd
February 2018: 10 on the 5th
March 2018: 20 on the 10th
April 2018: 25 on the 8th

Highest Daily Precipitation By Month
October 2017: 1.14″ on the 8th
November 2017: 1.72″ on the 5th
December 2017: 0.72″ on the 23rd
January 2018: 0.66″ on the 12th
February 2018: 1.23″ on the 24th
March 2018: 0.83″ on the 1st
April 2018: 2.06″ on the 15th

Precipitation Records
-The 1.14″ on the October 8th was the record for the date, beating the old record of 0.92″ set in 1959.
-The 1.72″ on November 5th was the record for the date, beating the old record of 0.88″ set in 1988.
-The 1.95″ on April 3rd was a record for the date, beating the old record of 1.50″ set in 2000.
-The 2.06″ on April 15th was a record for the date, beating the old record of 1.46″ set in 1939.

Highest Daily Snowfall By Month
October 2017: Trace on the 28th
November 2017: Trace on the 22nd
December 2017: 2.1″ on the 30th
January 2018: 3.5″ on the 12th
February 2018: 4.4″ on the 7th
March 2018: 0.9″ on the 21st
April 2018: 0.9″ on the 1st

Snowfall Records
-The 4.4″ on February 7th was a record for the date, beating the old record of 3.6″ set in 1895.
-The 0.9″ on March 21st was a record for the date, beating the old record of 0.8″ set in 1984.

Deepest Snow Depth By Month
October 2017: 0″
November 2017: 0″
December 2017: 3″ on the 30th and 31st
January 2018: 5″ on the 16th and 17th
February 2018: 4″ on the 7th
March 2018: 1″ on the 8th, 14th and 21st
April 2018: 1″ on the 2nd and 7th

So overall, the winter was definitely warmer than normal, but not record-breaking, even with the extremely warm February. It was also wetter and snowier than normal as well.

To see other winter records and local weather information, check out the following links.
Winter Season Records
Wilmington National Weather Service

Other Winter Reviews
Winter 2016-2017
Winter 2015-2016
Winter 2014-2015