Feels-Like Temperature Range 2014-2015.

Earlier in the summer I posted maps showing the "typical" range of temperatures during a climatological period. This post is a little different as it uses the "feels like" temperatures during the last year to depict the actual range of apparent temperatures. I use the conventional measures of Heat Index for warm temperatures and Wind Chill for cold temperatures. Only those stations that had sufficient observations to measure both a summer Heat Index and a winter Wind Chill were utilized. That required valid temperature, dewpoint (for Heat Index) and wind (for Wind Chill) measurements.

Heat Index:

The first map (Figure 1) shows the highest Heat Index recorded at ASOS station during the summer of 2015. The Heat Index was computed from hourly ASOS observations using the temperature and dew point (Steadman formula). The maximum dew point for 2015 is shown in Figure 2.

Figure 1. Highest Heat Index recorded in 2015 at ASOS stations.

Figure 2. Highest dew point temperature recorded in 2015 at ASOS stations.

Wind Chill:

Wind Chill is the apparent temperature based on the combined effect of temperature and wind. As many readers know, the wind chill formula was updated in 2001 (Osczevski 2001). In this analysis, I looked as hourly ASOS observations and computed wind chills for every hour during the 2014-2015 winter (November through March). The results are shown in Figure 3.

 Figure 3. Lowest Wind Chill recorded in the 2014-2015 winter at ASOS stations.

Range:

Unsurprisingly, continental climates experience the greatest range of annual temperatures (see interior Alaska and the northern Great Plains. While interior Alaska has the greatest annual temperature range in the U.S. based on climatology, several stations in North Dakota won the feels-like temperature lottery. In Alaska, the coldest temperatures are usually accompanied by calm winds and the warmest summer temperatures usually are so dry that the apparent temperature is 5°F-10°F lower than the actual temperature.

The other surprising aspect to the map is the range in Iowa is greater than the range in neighboring Nebraska.

Figure 4. Difference between highest Heat Index and Lowest Wind Chill at ASOS stations during the last year (summer minus winter).

Figure 5. ASOS stations used in the analysis depicted in Figures 1-4.

NWS Office Facebook and Twitter Update

Every six months or so I take a look at the social media presence of the 118 National Weather Service forecast office (not including San Juan, Guam, and American Samoa). The previous analysis of both the Facebook and Twitter followers is located here ( http://us-climate.blogspot.com/2015/03/nws-social.html ). Please note that the three Alaska NWS Office share a single Facebook page, yet have separate Twitter pages. In lieu of a complete replication of the March 28th post, I want to show a snapshot of where things stand as of now.

A note of caution. While rankings are labeled on the maps, and while it is human nature to make comparisons, keep in mind that the needs and demographics of each WFO are different.

Facebook:

The three Facebook maps below show the raw number of Likes (Figure 1), the rate of Likes per 100,000 population (Figure 2), and the change in Likes over the last six months (Figure 3).

Figure 1. Facebook Likes for 118 National Weather Service forecast offices as of September 28, 2015. Rank label (highest to lowest) added to each WFO.

Figure 2. Facebook Likes per 100,000 population for 118 National Weather Service forecast offices as of September 28, 2015. Rank label (highest to lowest) added to each WFO.

Figure 3. Rate of change of Facebook Likes for 118 National Weather Service between March 28, 2015, and September 28, 2015. Percent change labelled for each WFO.


Twitter

Twitter functions quite a bit differently than Facebook. While Facebook is a more casual source of information, Twitter is much more like a news aggregation site. The information is short, sweet, and timely. My experience has been that Twitter is much more of a specialized type of social media where the participants are in the media, celebrities, actors, athletes, and subject matter specialists.

So, here are my two maps for Twitter. The first (Figure 4, shows the number of Twitter followers for each NWS page. The second show the average number of Tweets sent out by those offices since their Twitter account was activated (Figure 5).

Figure 4. Twitter followers for 120 National Weather Service forecast offices as of September 28, 2015. Rank label (highest to lowest) added to each WFO. (Alaska offices separated out).

Figure 5. Twitter followers per 100,000 population for 120 National Weather Service forecast offices as of September 28, 2015. Rank label (highest to lowest) added to each WFO. (Alaska offices separated out).

Figure 6. Number of Tweets per month sent by the 118 National Weather Service forecast offices as of September 28, 2015. Rank label (highest to lowest) added to each WFO. Value computed by dividing number of tweets by number of months since page's inception. (Alaska offices combined).


Table 1. Raw count of Facebook Likes, Twitter Followers, Tweets, and rate of Tweets by National Weather Service Forecast Office (WFO). Separate entries made for the Alaska WFOs so that Twitter statistics are identifiable. They share identical Facebook values.

WFO	FB Likes	Twitter Followers	Total Tweets	Tweets / Month
Aberdeen	9,463	3,425	2,285	58.0
Albany	28,481	5,789	5,438	141.6
Albuquerque	9,165	5,279	11,200	258.3
Amarillo	39,288	7,792	3,984	101.2
Anchorage	43,699*	4,951	2,501	65.8
Austin/San Antonio	16,336	10,300	8,812	218.1
Baltimore/Washington	38,992	10,700	4,705	133.0
Billings	14,186	3,464	4,207	104.1
Binghamton	85,197	7,283	9,264	254.8
Birmingham	78,009	17,100	12,000	297.0
Bismarck	20,592	3,312	4,601	113.9
Blacksburg	22,607	5,785	8,358	223.6
Boise	15,107	3,918	2,752	77.8
Boston	72,275	32,700	17,200	447.9
Brownsville	23,898	4,147	6,063	150.1
Buffalo	10,694	7,841	1,900	56.9
Burlington	20,503	5,827	6,228	162.2
Caribou	28,668	2,421	8,889	274.8
Charleston (SC)	8,401	10,200	9,228	176.0
Charleston (WV)	29,944	5,118	1,871	47.5
Cheyenne	11,719	2,924	4,455	113.1
Chicago	112,556	20,800	11,400	296.9
Cleveland	15,679	5,954	2,655	67.4
Columbia	12,292	3,848	5,199	109.7
Corpus Christi	10,188	4,535	3,763	93.1
Dallas/Fort Worth	102,441	39,000	12,800	316.8
Davenport/Quad Cities	13,380	4,816	3,289	83.5
Denver/Boulder	16,615	11,400	6,047	153.5
Des Moines	29,778	9,979	7,981	202.6
Detroit/Pontiac	12,259	6,026	3,273	83.1
Dodge City	9,820	4,291	6,904	170.9
Duluth	8,838	2,204	2,594	75.5
El Paso	5,971	4,317	9,264	213.6
Elko	6,943	2,285	7,386	182.8
Eureka	11,549	3,051	5,909	146.2
Fairbanks	43,699*	2,600	1,967	51.8
Flagstaff	11,660	6,286	4,175	103.3
Gaylord	9,822	2,808	9,675	245.6
Glasgow	10,538	2,507	2,097	51.9
Goodland	7,509	3,446	6,866	174.3
Grand Forks	10,075	3,124	3,334	84.6
Grand Junction	5,631	2,249	5,073	143.4
Grand Rapids	19,710	5,550	3,772	95.8
Gray/Portland	13,048	4,679	6,611	172.2
Great Falls	7,913	3,458	9,199	227.7
Green Bay	8,392	3,916	2,409	59.6
Greenville-Spartanburg	15,602	4,995	5,253	133.4
Hastings	19,210	4,365	7,453	189.2
Honolulu	17,248	8,050	1,722	32.8
Houston/Galveston	18,024	11,400	6,037	153.3
Huntsville	27,619	10,900	4,687	116.0
Indianapolis	20,747	14,900	8,245	209.3
Jackson (KY)	12,760	3,855	7,853	199.4
Jackson (MS)	75,295	13,200	14,400	356.4
Jacksonville	8,456	4,052	4,787	118.5
Juneau	43,699*	2,109	7,627	200.7
Kansas City/Pleasant Hill	82,302	24,100	9,481	180.8
Key West	28,081	7,863	4,226	104.6
La Crosse	12,270	4,006	6,022	152.9
Lake Charles	11,115	3,338	5,264	130.3
Las Vegas	10,593	8,844	9,026	223.4
Lincoln	30,948	6,647	4,746	120.5
Los Angeles/Oxnard	18,945	15,800	8,195	208.1
Louisville	21,372	8,868	8,821	224.0
Lubbock	8,155	5,680	5,272	130.5
Marquette	16,743	4,003	3,722	92.1
Medford	12,430	2,739	1,427	35.3
Melbourne	13,314	5,086	4,148	102.7
Memphis	22,413	9,820	9,628	238.3
Miami	15,069	13,300	8,395	207.8
Midland/Odessa	12,836	3,416	8,470	209.6
Milwaukee/Sullivan	25,652	5,169	4,797	121.8
Minneapolis/Twin Cities	23,455	15,400	10,300	261.5
Missoula	8,757	3,586	9,657	239.0
Mobile/Pensacola	25,052	14,400	12,200	301.9
Morristown/Knoxville	18,615	3,874	3,198	79.1
Mount Holly/Philadelphia	67,482	17,300	2,637	67.0
Nashville	55,707	13,600	14,200	360.5
New Orleans/Baton Rouge	32,068	7,587	6,010	148.7
New York	46,268	24,600	8,252	209.5
Newport/Morehead City	12,505	2,941	5,538	152.3
Norman/Oklahoma City	173,839	53,000	14,200	390.5
North Little Rock	64,215	19,100	2,861	70.8
North Platte	7,658	3,677	7,308	185.5
Northern Indiana	40,180	10,100	11,200	284.4
Omaha/Valley	13,283	8,778	4,701	119.4
Paducah	44,807	10,100	8,107	205.8
Peachtree City/Atlanta	26,782	10,300	4,377	108.3
Pendleton	9,201	2,461	2,052	52.1
Phoenix	10,567	10,500	6,978	172.7
Pittsburgh	48,433	13,500	5,404	144.6
Pocatello	4,014	2,465	9,095	225.1
Portland	19,633	6,893	5,465	142.3
Pueblo	5,939	3,805	5,377	133.1
Raleigh	12,545	7,873	3,471	92.9
Rapid City	11,519	3,452	1,306	33.2
Reno	14,657	4,833	5,024	124.3
Riverton	10,841	2,004	7,613	193.3
Sacramento	18,599	10,200	11,900	302.1
Salt Lake City	8,052	10,200	10,400	257.4
San Angelo	16,336	4,636	5,234	129.5
San Diego	13,427	6,355	12,500	288.3
San Francisco Bay Area/Monterey	18,989	17,100	16,800	426.5
San Joaquin Valley/Hanford	14,739	4,204	11,500	284.6
Seattle	12,839	7,670	2,812	73.2
Shreveport	29,533	4,069	11,500	292.0
Sioux Falls	21,464	10,300	7,619	188.6
Spokane	12,318	4,618	5,673	70.6
Springfield	27,260	8,964	4,706	119.5
St. Louis	36,715	8,564	3,002	74.3
State College	20,811	5,744	8,544	216.9
Tallahassee	8,964	6,782	6,249	154.7
Tampa	14,837	7,810	12,800	316.8
Topeka	13,285	7,880	4,356	107.8
Tucson	6,378	5,493	6,606	163.5
Tulsa	41,225	11,100	7,171	139.5
Wakefield	8,864	2,531	635	21.6
Wichita	33,731	14,000	7,561	192.0
Wilmington (NC)	8,780	5,200	2,116	59.8
Wilmington (OH)	39,268	11,500	5,548	140.9