Extreme Minimum Winter Temperatures in Ohio · 2006-07-08 · Celina 3 NE Centerburg Chardon...
14
Extreme Minimum Winter Temperatures in Ohio 1 DENNIS J. EDGELL, DEPARTMENT OF GEOGRAPHY, Firelands College, Bowling Green State University, Huron, OH 44839 ABSTRACT. The Extreme Minimum Winter Temperature (EMWT) is the coldest temperature recorded each winter at a given weather station. This variable is a measure of winter temperature severity. EMWT influences the geographic distribution of plants, and is a prime control for the production of some fruit crops grown in Ohio. EMWT values are often used to map plant hardiness zones, but climatic variables rarely remain constant over time, and plant hardiness zones could shift significantly if the climate of Ohio changes and there is a change in EMWTs. EMWTs from 89 weather stations in Ohio were analyzed to determine spatial patterns and time trends. Summary statistics of EMWTs were tabulated and mean EMWT was mapped at a large scale. Linear and polynomial regression were utilized to examine thetime series. EMWTs have not warmed during the climatic record of this variable. There does not appear to be a link between EMWTs in Ohioand the increasing levels of CO 2 in the atmosphere. The present study demonstrates theneed for more research in applied climatology based on observed climate records, not obscured by the assumptions of the global warming paradigm. OHIO J. SCI. 94 (3): 41-54, 1994 INTRODUCTION Ohio is located in the midlatitudes and experiences a generally temperate climate typical of the American Mid- west. The position of the state near the middle of the North American continent produces a climate type suitable to support and maintain a large human population, extensive urban systems, and agricultural development. Average winter and summer temperatures are neither severely cold nor oppressively hot for most human activities. However, the midlatitude humid continental climate exhibits a wide range of extreme temperatures and sig- nificant intra-seasonal variability in temperature. Notable extremes of heat and cold have occurred in the past, and it is these extremes of temperature—especially cold winter temperatures—that determine the geographic ranges of many plants. In the study of regional climates, averages and normals are important statistical descriptions of climate, but in some circumstances extreme values are of greater importance. The lowest temperature that occurs during winter at a given geographic location, known sometimes as the annual minimum temperature, or as the Extreme Mini- mum Winter Temperature (EMWT), is of considerable interest to climatologists. Perennial plants, such as tender fruit crops, ornamental species, and pest vines, are limited in range less by the annual average temperature than by the EMWT. Plant distributions are influenced by the coldest survivable temperature characteristic of a given environment. Extreme cold can hinder or even halt biochemical and other physiological actions, thus the magnitude of EMWT is a fundamental characteristic of the temperature climatology of any environment. For the cultivation of fruit crops, EMWT is a factor as critical as length of growing season, precipitation distribution, and edaphic conditions. Small scale maps of average EMWT have been published by the United States Department of Agriculture (1990). Knowledge of the magnitude, variability, 'Manuscript received 16 September 1993 and in revised form 29 March 1994 (#93-21). and distribution of EMWT has applications in other fields as well. Designers take into account the coldest temperature which can occur at a given location, and the potential impact of this on structures and occupants (Rizzi 1980). If the expected EMWT changes over time, or if EMWTs become more or less variable, then the geographic distribution of certain plant species could change as well. The subject of global warming and climate change associated with an enhanced "greenhouse effect" is of considerable scientific and popular interest (Jones and Henderson-Sellers 1990). It is well known that climate changes over time scales of thousands and millions of years, but significant climatic changes and trends on a "generational" time scale (a few decades) may also occur. The proponents of greenhouse warming warn that the earth's climate will warm several degrees in the next few decades, and also alert us that this warming is already under way, as exhibited by the known climate record 0ones andWigley 1990). A wine and fruit industry more lucrative than the present would be onearguable benefit of "global warming" since the ranges of tender fruit could be extended further from Lake Erie. Conversely, pest vines such as Kudzu vine, which grows rampant in the south- eastern states but is presently limited by cold northern winters, could extend its range northward into Ohio if EMWTs become warmer (Sasek and Strain 1990). The time series and trends of EMWT are thus an issue in Ohio climatology. A question remains as to whether EMWTs in Ohio have become warmer or cooler over recent decades. Even if climatic averages are not changing, an increase in the frequency of extreme events could be indicative of climate change. The objective of the present study is to quantify the magnitude geographic variability of EMWT in Ohio, and to assess the overall time series trend of this variable. The present study provides a statistical analysis, climatic sum- mary, and rationale for geographic explanation of extreme minimum winter temperatures in Ohio. Although extreme values in a local area may not match a global trend, the present study is one piece in the climate change puzzle.
Transcript of Extreme Minimum Winter Temperatures in Ohio · 2006-07-08 · Celina 3 NE Centerburg Chardon...
Extreme Minimum Winter Temperatures in Ohio1
DENNIS J. EDGELL, DEPARTMENT OF GEOGRAPHY, Firelands College, Bowling Green State University, Huron, OH 44839
ABSTRACT. The Extreme Minimum Winter Temperature (EMWT) is the coldest temperature recorded eachwinter at a given weather station. This variable is a measure of winter temperature severity. EMWT influencesthe geographic distribution of plants, and is a prime control for the production of some fruit crops grownin Ohio. EMWT values are often used to map plant hardiness zones, but climatic variables rarely remainconstant over time, and plant hardiness zones could shift significantly if the climate of Ohio changes andthere is a change in EMWTs. EMWTs from 89 weather stations in Ohio were analyzed to determine spatialpatterns and time trends. Summary statistics of EMWTs were tabulated and mean EMWT was mapped at a largescale. Linear and polynomial regression were utilized to examine the time series. EMWTs have not warmedduring the climatic record of this variable. There does not appear to be a link between EMWTs in Ohio andthe increasing levels of CO2 in the atmosphere. The present study demonstrates the need for more researchin applied climatology based on observed climate records, not obscured by the assumptions of the globalwarming paradigm.
OHIO J. SCI. 94 (3): 41-54, 1994
INTRODUCTIONOhio is located in the midlatitudes and experiences a
generally temperate climate typical of the American Mid-west. The position of the state near the middle of the NorthAmerican continent produces a climate type suitable tosupport and maintain a large human population, extensiveurban systems, and agricultural development. Averagewinter and summer temperatures are neither severelycold nor oppressively hot for most human activities.However, the midlatitude humid continental climateexhibits a wide range of extreme temperatures and sig-nificant intra-seasonal variability in temperature. Notableextremes of heat and cold have occurred in the past, and itis these extremes of temperature—especially cold wintertemperatures—that determine the geographic ranges ofmany plants. In the study of regional climates, averagesand normals are important statistical descriptions ofclimate, but in some circumstances extreme values are ofgreater importance.
The lowest temperature that occurs during winter ata given geographic location, known sometimes as theannual minimum temperature, or as the Extreme Mini-mum Winter Temperature (EMWT), is of considerableinterest to climatologists. Perennial plants, such as tenderfruit crops, ornamental species, and pest vines, are limitedin range less by the annual average temperature than bythe EMWT. Plant distributions are influenced by thecoldest survivable temperature characteristic of a givenenvironment. Extreme cold can hinder or even haltbiochemical and other physiological actions, thus themagnitude of EMWT is a fundamental characteristic ofthe temperature climatology of any environment. For thecultivation of fruit crops, EMWT is a factor as critical aslength of growing season, precipitation distribution, andedaphic conditions. Small scale maps of average EMWThave been published by the United States Department ofAgriculture (1990). Knowledge of the magnitude, variability,
'Manuscript received 16 September 1993 and in revised form 29March 1994 (#93-21).
and distribution of EMWT has applications in other fieldsas well. Designers take into account the coldest temperaturewhich can occur at a given location, and the potentialimpact of this on structures and occupants (Rizzi 1980).
If the expected EMWT changes over time, or if EMWTsbecome more or less variable, then the geographicdistribution of certain plant species could change as well.The subject of global warming and climate changeassociated with an enhanced "greenhouse effect" is ofconsiderable scientific and popular interest (Jones andHenderson-Sellers 1990). It is well known that climatechanges over time scales of thousands and millions ofyears, but significant climatic changes and trends on a"generational" time scale (a few decades) may also occur.The proponents of greenhouse warming warn that theearth's climate will warm several degrees in the next fewdecades, and also alert us that this warming is alreadyunder way, as exhibited by the known climate record0ones and Wigley 1990). A wine and fruit industry morelucrative than the present would be one arguable benefitof "global warming" since the ranges of tender fruit couldbe extended further from Lake Erie. Conversely, pest vinessuch as Kudzu vine, which grows rampant in the south-eastern states but is presently limited by cold northernwinters, could extend its range northward into Ohio ifEMWTs become warmer (Sasek and Strain 1990). The timeseries and trends of EMWT are thus an issue in Ohioclimatology. A question remains as to whether EMWTs inOhio have become warmer or cooler over recentdecades. Even if climatic averages are not changing, anincrease in the frequency of extreme events could beindicative of climate change.
The objective of the present study is to quantify themagnitude geographic variability of EMWT in Ohio, andto assess the overall time series trend of this variable. Thepresent study provides a statistical analysis, climatic sum-mary, and rationale for geographic explanation of extrememinimum winter temperatures in Ohio. Although extremevalues in a local area may not match a global trend, thepresent study is one piece in the climate change puzzle.
42 EXTREME MINIMUM WINTER TEMPERATURES IN OHIO VOL. 94
MATERIALS AND METHODSSite Description
Ohio is a typical midwestern state and has grownparallel to the national trends of population growth, theremoval of the climax vegetation, urban expansion andsuburban sprawl, industrial growth, some agriculturalabandonment, and a shift to a postindustrial society.Furthermore, Ohio has an extensive network of temperaturerecording stations with an accumulation of sufficientstandardized data to determine temperature trends thathave occurred in the past several decades. There are 89stations with at least 30 years of continuous EMWT data(Fig. 1). These stations are well distributed throughout thestate (Table 1), and should represent minimumtemperatures as they occur in Ohio.
Data CollectionThe extreme minimum winter temperature (EMWT) is
defined as the lowest daily minimum temperature (TMIN)observed for each winter at a given weather station. Dailyminimum and daily maximum air temperatures are recordedat the seven National Weather Service (NWS) observingstations in Ohio, but the majority of data are collected bya network of volunteer observers at "cooperative" stationslocated throughout the state (Fig. 1). At cooperative
40 80
FIGURH 1. Locations of Ohio weather stations with at least 30 years of con-tinuous extreme minimum winter temperature data. Dark lines indicateclimatic division boundary. (See Table 1 for station number index.)
TABLE 1
Index of Ohio weather stations utilized for the analysis of extreme minimum winter temperatures in Ohio.
MapNo.
123
4567
89
101112131415161718192021222324
252627
StationName*
Akron-Canton WSO APAshland 2 SWAshtabula
BarnesvilleBellefontaineBowling GreenBucyrus
CadizCaldwell 6 NWCambridgeCanfieldCelina 3 NECenterburgChardonCharles Mill LakeChilo Meldahl LockChippewa LakeCin Muni-Lunken FidCirclevilleCleveland WSFO APColumbus Valley X-ingColumbus WSO ApCoshocton 3 SSWCoshocton Agr Rsch St
Dayton (City)Dayton WSO ApDefiance
ClimateDivision
NortheastCentral HillsNortheast
SoutheastWest CentralNorthwestNorth Central
Northeast HillsSoutheastSoutheastNortheast HillsWest CentralCentral HillsNortheastCentral HillsSouthwestNortheastSouthwestCentralNortheastCentralCentralCentral HillsCentral Hills
SouthwestSouthwestNorthwest
County
SummitAshlandAshtabula
BelmontLoganWoodCrawford
HarrisonNobleGuernseyMahoningMercerKnoxGeaugaAshlandClermontMedinaHamiltonPickawayCuyahogaFranklinFranklinCoshoctonCoshocton
MontgomeiyMontgomeryDefiance
404041
39404140
4039404140404140384139394139404040
393941
Lat.0 'N
555051
58212349
16490101341835444804063725540
1522
465417
Long.
818280
81838382
8181818084828182848184828182828181
848484
W
262148
09463758
036354632391122105426575254535248
111223
Elev.
Cm)
362380207
375356203287
378294240342257362339308150318146202231225244228342
224299210
OHIO JOURNAL OF SCIENCE D. G. EDGELL 43
TABLE 1 {Continued)
Index of Ohio weather stations utilized for the analysis of extreme minimum winter temperatures in Ohic
MapNo.
StationName*
ClimateDivision County
Lat.° 'N
Long.° 'W
Elev.(m)
2829
3031
3233343536
3738
394041
4243
44
45
464748
4950515253545556
5758596061
DelawareDorset
EatonElyria 3 E
Findlay FAA ApFind lay WPFranklinFredericktown 4 SFremont
GallipolisGreenville Water Pit
HillsboroHiramHoytville
IrontonIrwin
Jackson 2 NW
Kenton
Lancaster 2 NWLima Sewage PlantLondon Water Works
Mansfield WSO ApMansfield 5 WMarion 2 NMarysvilleMcConnelsville LockMillport 2 NWMineral Ridge Wtr WksMontpelier
NapoleonNewark Water WorksNew Lexington 2 NWNew PhiladelphiaNorwalk
62 Oberlin
636465666768
69
70717273
Painesville 4 NWPandoraPauldingPhilo 3 SWPortsmouthPut-in-Bay Perry Mon
Ripley Exp Farm
SanduskySenecaville LakeSidney 1 SSteubenville
CentralNortheast
SouthwestNorth Central
NorthwestNorthwestSouthwestCentral HillsNorth Central
South CentralWest Central
SouthwestNortheastNorthwest
South CentralCentral
South Central
West Central
Central
NorthwestCentral
Central HillsCentral HillsCentralCentralSoutheastNortheast HillsNortheastNorthwest
NorthwestCentralSoutheastNortheast HillsNorth Central
North Central
NortheastNorthwestNorthwestSoutheastSouth CentralNorth Central
Southwest
North CentralSoutheastWest CentralNortheast Hills
DelawareAshtabula
PrebleLorain
HancockHancockWarrenKnoxSandusky
GalliaDarke
HighlandPortageWood
LawrenceUnion
Jackson
Hardin
Fairfield
AllenMadison
RichlandRichlandMarionUnionMorganColumbiaTrumbullWilliams
HenryLickingPerryTuscarawasHuron
Lorain
LakePutnamPauldingMuskingumSciotoOttawa
Brown
ErieGuernseyShelbyJefferson
4041
3941
4141394041
3840
394141
3840
1741
4423
0103332520
4906
121813
3207
39 04
40 39
394039
4040404039404141
4140394041
444353
4946371439430935
2205443016
41 16
414041393841
455707504539
8380
8482
8383848283
8284
838183
8283
82
83
828483
8282838381808084
8482828182
0440
3803
4040193207
1139
370946
4029
39
36
380827
3137082251544736
0925132737
82 13
818384818282
185836555348
38 47
41 2739 5540 1640 23
83 48
82818480
43260938
260294
301219
239230201315180
173307
330369210
201303
210
299
258255306
389405290301198344267258
205251267270201
245
180231218306162174
264
175263281298
74 Tiffin North Central Seneca 41 07 83 10 221
44 EXTREME MINIMUM WINTER TEMPERATURES IN OHIO VOL. 94
TABLE 1 (Continued)
Index of Ohio weather stations utilized for the analysis of extreme minimum winter temperatures in Ohio.
MapNo.
757677
7879
8081
82
83848586
87
88
89
StationName*
Toledo Express WSO ApToledo BladeTom Jenkins Lake
LJpper SanduskyUrbana Sewage Plant
Van WertWarren 3 S
Wauseon Water PlantWaverlyWestervilleWilmington 3 NWooster Exp Station
Xenia 6 SSE
Youngstown WSO Ap
Zanesville FAA Ap
ClimateDivision
NorthwestNorthwestSoutheast
North CentralWest Central
NorthwestNortheast
NorthwestSouth CentralCentralSouthwestCentral Hills
Southwest
Northeast
Southeast
County
LucasLucasAthens
WyandotChampaign
Van WertTrumbull
FultonPikeFranklinClintonWayne
Greene
Trumbull
Muskingum
Lat.
414139
4040
4041
413940
3940
39
41
39
353933
5006
5012
310708
2947
37
15
57
Long.
838382
8383
8480
848282
8381
83
80
81
W
483204
1747
3449
0959574955
54
40
54
Elev.(m)
201
179228
256300
237270
225168243309306
290
353
264
*From Climatological Data—Ohio, National Climatic Data Center (1990).
stations, special "maximum-minimum thermometers"record the highest and lowest twenty-four hour tempera-tures, and the thermometers are reset daily. The EMWTvalue is that daily minimum temperature that is the low-est in the annual series from 1 July of one year to 30 Juneof the following year. Rather than analyzing the annual(calendar year) minimum of previous studies, this "fiscalyear" approach better represents the continuum ofwinter conditions present through individual winters.
All temperature data were originally collected in de-grees Fahrenheit, but these were converted to degreesCelsius, and rounded to the nearest tenth of a degree(Celsius) before statistical analysis, and the major findingsof the study are reported in Celsius. The time periodunder investigation is from the winter 1870-71 to 1989-1990, but most stations used in this study do not have databefore 1900. Stations with at least 30 years of EMWT datawere considered for the analysis. The NWS TMIN valueswere obtained from computer data tapes supplied by theKent State University Climatology Laboratory, and theOhio Agricultural Research and Development Center.Additionally, published sources of daily TMIN values wereutilized. These include Climatological Data: Ohio and theOhio Section of Climatological Data, and from the tablesoriginally published by Alexander (1923).
Statistical MethodsDescriptive statistics were calculated using the SAS 5.0
(1985) statistical analysis package. Formulae for theunivariate statistical procedures (mean, standard deviation,etc.) are not listed in the SAS manual; however, the text for
geographers by Clark and Hosking (1986) was useful forinterpretation of statistical methods. The Shapiro-Wilk testwas utilized to test all variables for normality (P <0.05).Data plotting, linear regression, and polynomial regres-sion over time were used to examine the time series.Formulae are clarified in Zar (1984). All significance testswere made at the 95% confidence level by convention(Clark and Hosking 1986).
A state isotherm map of EMWT "normals" was drawn.A climatic "normal" is a 30 year average; the most recent"normal period" being the winter 1960-61 to 1989-90.
RESULTSDescriptive Statistics
All data for each station fit the normal frequencydistribution. The univariate statistics were surprisinglyuniform throughout Ohio. A pooled standard deviation of3.99° C was characteristic of Ohio EMWT. The coldestEMWT in the entire data set was -36.7° C for Sidney (WestCentral Division), recorded during January 1884, and thewarmest was -9.4° C at Portsmouth (South Central),recorded 11 February 1937. Generally, the NortheastDivision stations were coldest (Table 2), so it is note-worthy that the record coldest EMWT was found in westcentral Ohio. It was not surprising that the warmestEMWT was recorded at one of the most southerly locations.As expected, stations along the lakeshore or along thesouthern boundary had the warmest mean EMWT. Overmuch of Ohio, the mean EMWT was between -22° C and-24° C. A general latitudinal gradation was seen, es-pecially in the South Central Division, where the isotherm
OHIO JOURNAL OF SCIENCE D. G. EDGELL
TABLE 2
Descriptive statistics for extreme minimum winter temperatures in Ohio.
45
NORTH WEST DIVISIONBowling Green Swg PiDefianceFindlay FAA APFindlay Sewage PlantHoytvilleLima Sewage PlantMontpelierNapoleonPandoraPauldingToledo Express WSO ApToledo BladeVan WertWauseon Water Plant
NORTH CENTRAL DIVISIONBucyrusElyriaFremontNorwalkOberlinPut-In-Bay Perry MonSanduskyTiffinUpper Sandusky
NORTH EAST DIVISIONAkron-Canton WSO APAshtabulaChardonChippewa LakeCleveland WSO APDorsetHiramMineral Ridge Wtr WksPainesville 4 NWWarren 3 SYoungstown WSO AP
WEST CENTRAL DIVISIONBellefontaine SewageCelina 3 NEGreenville Water PitKentonSidney 1 SUrbana Sewage Plant
CENTRAL DIVISIONCirclevilleColumbus Valley X-ingColumbus WSO APDelaware LakeIrwinLancasterLondon Water WorksMarion 2 NMarysvilleNewark Water WorksWesterville
N
967742
933889885241
55369171
120
96413864
106
63107104108
4239455542349751419842
913497
1004495
74424268
49895480555537
X
-22.49-22.96-21.89-22.24-23.48-21.98-23.33-23.43-23.24-23.35-23.25-19.96-22.47-23.98
-22.97-22.10-21.95-23.18-22.54
-19.65-19.76
-21.39-22.06
-21.68-20.24-23.67-22.98-20.88-26.22-21.82-22.18-19.02
-22.55-21.62
-23.22-23.30-22.62-22.87-23.63-22.93
-21.00-21.41-21.01-22.16
-23.39-22.16-22.47-22.54-22.44-22.26-24.06
5"
3.53.53.63.63.23.43.73.63.33.53.23.83.54.2
3.6
3.33.14.23.84.13.63.53.6
3.93.34.0
3.33.72.73.73.63.54.03.5
3.73.63.83.64.73.9
4.14.44.0
3.93.64.43.83.64.0
4.34.7
Record
Low
-30.0-32.2
-28.3-29.4-30.0-29.4-31.7-31.1-30.6-31.7-28.9-26.7-30.0-35.6
-33.3-28.3-27.8-31.7-30.6-27.2-27.2
-28.9-30.0
-31.1-27.2-32.2-29.4
-28.3-33.3-30.6-28.9-26.1-32.2
-28.9
-30.6-30.6-32.2
-31.1-36.7-32.2
-30.6-30.0-28.3-32.8
-31.1-31.1-30.6-30.6-30.6-32.2-32.8
High
-15.6-15.0-15.0-15.0-17.8-15.0-15.0-16.1-15.6-16.7-16.1-12.2-15.0-14.4
-13.9-14.4-15.0-15.0-14.4-11.1-11.1-14.4-15.6
-15.6-13.3-16.1-15.0-14.4-21.7-15.0-13.3-12.2
-13.9-15.0
-15.0-16.7-15.0-16.1-17.2
-13.3
-12.8-13.9-14.4
-13.9-15.6-12.8-15.6
-13.3-13.9-13.3-15.6
10thprctl
-27.8-27.8-27.7-28.1-28.9-27.2
-27.9-28.8-27.8-28.5-27.2-25.6-27.8-29.4
-27.8-26.1-27.2-29.4-27.8-25.6-25.1-26.7-27.2
-28.2-25.4-30.0-27.1-27.2-29.7-26.7-27.2
-24.9-27.8-26.5
-28.9-28.6-27.9-27.8-30.6-28.3
-27.5-28.9-26.7-27.3-28.9-28.9-27.8-27.2
-28.5-28.5-31.7
30 yearNormal x(1961-90)
-22.58-24.05-22.70-22.94-23.84-23.33-24.44-23.02-23.83-24.06-23.83-20.44-23.02-24.43
-23.29-22.50-22.45
—-23.72-20.35-20.95-22.42-22.68
-22.37-21.20-25.40-24.03-21.71-26.68-22.41-23.01-19.66-24.52-22.53
-24.01-23.46-24.44
-23.35—
-23.80
-21.66-22.05-21.62
-23.53-23.96-22.86-22.97-23.71-23.07-22.30-24.81
46 EXTREME MINIMUM WINTER TEMPERATURES IN OHIO VOL. 94
TABLE 2 (Continued)
Descriptive statistics for extreme minimum ivinter temperatures in Ohio.
CENTRAL HILLS DIVISIONAshland 2 WCenterburg 2 SECharles Mill LakeCoshocton Sewage PitCoshocton Agri RschFredericktown 4 SMansfield WSO APMansfield 5 WWooster Exp Station
NORTH EAST HILLS DIVISIONCadizCanfield 1 SMillport 2 NWNew PhiladelphiaSteubenville
SOUTH WEST DIVISIONChilo-Meldahl Lock DamCin Muni-Lunken FidDaytonDayton WSO APEatonFranklinHillsboroRipley Exp FarmWilmington 3 NXenia 6 SSE
SOUTH CENTRAL DIVISIONGallipolisIronton 1 NEJackson 2 NWPortsmouthWaverly
SOUTH EAST DIVISIONBarnesville-Frds SchCaldwell 6 NWCambridge Water PlantMcConnelsville Lock 7New Lexington 2 NWPhilo 3 SWSenecaville LakeTom Jenkins LakeZanesville FAA AP
TV
8439495534413942
107
8773693049
5335
10640353697316955
5510055
10055
504868974942483445
X
-22.17-23.57-24.14-21.53-21.92-24.27-21.96-25.48-22.52
-20.90-23.21-24.49-22.11-20.22
-20.00-19.20-20.19-22.22-23.69-21.82-21.29-21.71-22.03-22.08
-20.04-18.85-23.32-18.21-21.80
-24.07-22.30-22.81-21.50-23.73-20.92-23.07-24.92-21.40
3.43.94.04.43.64.13.73.63.6
3.93.93.93.63.7
4.34.44.14.04.74.34.04.64.34.7
4.44.45.14.14.8
4.24.34.74.44.63.94.73.93.7
Low
-29.4-30.6-33.3-28.9-29.4-32.2-30.0-33.9-31.1
-32.2-31.1-31.7-28.3-30.0
-29.4-28.9-33.3-31.1-34.4-31.7-30.6-30.6-31.7-33.3
-29.4-32.8-35.0-28.9-31.7
-31.7-30.6-36.1-33.9-32.2-28.3-34.4-32.8-28.3
RecordHigh
-14.4-17.2-15.6-12.2-15.6-16.7-16.1-18.9-13.9
-12.2-14.4-17.2-15.6-13.9
-12.2-12.2-11.7-15.6-16.7-15.6-12.2-13-9-15.6-12.2
-10.6-10.0-12.8-9.4
-11.7
-14.4-12.2-12.8-11.1-15.0-13.9-15.0-15.6-15.6
10thprctl
-27.2-30.0-28.9-28.3-28.3-30.5-28.9-30.0-27.8
-27.2-29.2-30.0-27.2-25.6
-26.7-26.0-26.3-28.9-31.1-29.1-27.8-28.8-29.4-28.5
-26.7-25.0-30.4-24.2-29.4
-28.9-28.9-28.4-27.8
-31.1-27.6-29.5-30.0-27.5
30 yearNormal x(1961-90)
-23.52-23.83-25.62-22.49-22.02-24.98-22.76-25.83-23.11
-21.91-25.77-25.84-22.11-20.98
-20.66-19.72-20.45-22.65-23.95-22.00-21.61-21.80-22.91-23.07
-20.75-19.44-24.69-19.80-22.68
-24.54-23.50
—-22.60-24.37-21.63
——
-21.99
N = Number of winters in station climate record.x = Mean extreme minimum winter temperature in degrees Celsius.5 = Standard deviation of extreme minimum winter temperatures in degrees Celsius.10th prctl = The tenth percentile of the entire extreme minimum winter temperature data for that station.Normal x = Thirty year mean for the time period 1961 to 1990.
gradient was steep. Portsmouth and Ironton (South Cen-tral Division) had the warmest mean EMWTs in Ohio. Afterlatitudinal location, proximity to Lake Erie was the mostimportant spatial control of EMWT. The lakeshore stations
were relatively mild, and there was a steep decrease inmean EMWT inland, especially in the Northeastern Divisionwhere the mean EMWT dropped from -19.02° C at Paines-ville to -26.22° C at Dorset. There was more geographic
OHIO JOURNAL OF SCIENCE D. G. EDGELL 47
variability of mean EMWT in the Northeastern Divisionthan in other portions of the state from the effects of LakeErie and the high terrain inland.
Over most of the flat western half of Ohio, the meanEMWT was between -22° C and -24° C, and the gradientwas gentle. The mean EMWT pattern in eastern Ohio wasmore complex because of the hilly topography, Lake Erie,and the Ohio River. Surprisingly, some relatively coldspots were located in southern Ohio. For example, TomJenkins Lake (Southeast Division) was located in a regionbroadly characterized by generally mild EMWTs, but thestation site was prone to cold air drainage. Despite itssoutherly latitude, this station exhibited some of thecoldest EMWTs in the state, quite different from thesurrounding stations.
Urban effects also had some influence on EMWT. In theNorthwest Division, a 3-4° C temperature difference wasobserved between the warmer urban Toledo station(Toledo Blade) and the cooler rural Toledo station (Ex-press Airport NWS Office). The proximity of the ToledoBlade station to Lake Erie also contributed to the contrast.A 2.2° C urban heat island effect was observed betweenthe two Dayton sites (Southwest Division). The urban heatisland effect on mean EMWT may help certain horti-cultural plants to survive through cooler periods—anarguable beneficial aspect of heat islands.
Site micro-characteristics influenced the EMWT in anylocation. Although the map (Fig. 2) was less generalizedthan the similar map produced by the U.S.D.A. (1990),further specificity at individual locations is possible onlyif site characteristics are known. Cold, dense air descendsdownslope on cold nights, therefore low spots are proneto colder EMWTs than the map indicates. This map (Fig.2) still represents a broad generalization of EMWT in Ohioand should be viewed with caution.
-26.2 to -28.8"C(-15 to -20°F)
23.4 to -26.1°C(-10 to -15°F)
-17.8 to -20.5°C(0 to -8°F
FIGURE 2. Map of mean extreme minimum winter temperature in Ohio(1960-61 to 1989-90 normal period). Isotherm categories are the planthardiness zones defined by the U.S.D.A. Isotherms are shown here indegrees Celsius.
The record low EMWT for each station was an interest-ing comparative statistic; however, the magnitude of therecord low EMWT was dependent on the length of stationrecord. The longer a station records temperature, thegreater the chance that a new, lower EMWT would havebeen recorded. A station with a long record had sampledmore outbreaks of Arctic air than a station with a shortrecord. Therefore, the record low EMWT was lower atstations with longer records, if all other factors were equal.The 10th percentile was the EMWT exceeded in 10% ofwinters. Few Ohio stations could have expected to have10% of their EMWTs below -30° C, but 71% of Ohiostations have recorded a temperature below -30° C at leastonce in their climate record.
Time Series AnalysisThe time series analysis revealed that Ohio EMWTs
were not serially correlated. Some trends were observablethrough data plotting. Generally, the early portions of thiscentury had cooler EMWTs, the 1930s had the warmestEMWTs, and there has been an overall cooling trendsince mid-century. The data plots (Fig. 3) for Sandusky(North Central Division) and Hiram (Northeast Division)reflected the overall pattern. The wide variability of EMWTon any given winter complicated the pattern, but allstations showed the general trend. At Sandusky, the plotshows that although there were some mild years duringthe 1980s, the 1980s also had two winters when the EMWT
S A N D U S K Y E M W T T I M E S E R I E SReference Line = -26°C (-15°F)
80 90 1900 10 20 30 40 50 60 70 80 1990
WINTERS: 1883-84 TO 1989-90
H I R A M E M W T T I M E S E R I E SReference Line = -26°C (-15°F)
80 1990
WINTERS: 1893-94 TO 1989-90
FIGURE 3. Example extreme minimum winter temperature plots for A: San-dusky, and B: Hiram, with reference to the critical temperature of-26.1° C.
TE
MP
ER
AT
UR
E
(°C
)
48 EXTREME MINIMUM WINTER TEMPERATURES IN OHIO VOL. 94
dipped below -26.1° C (the critical temperature for somegrapes, peaches, etc.), although in previous years it hadnever attained that degree of coldness.
The linear correlation and regression tests (Table 3)showed that Ohio EMWTs did not have a positive lineartrend; in fact, the Northeast Division had several stationswith cooling trends since mid-century (see ChippewaLake graph, Fig. 4). Stations with a test for the slope beta(B) that were greater than 1.96 or less than -1.96 weresignificant. Ten stations had a century of EMWT data,however, only the Dayton city station had a significantpositive (i.e., warming) linear slope (Fig. 5) and this mighthave been partially explained by the influence of urbanwarming. The linear tests for the recent normal period alsodid not show a warming of EMWT over time for moststations (Table 3).
C H I P P E W A L A K E E M W T T I M E S E R I E S
cj -20-
WINTERS 1935-46 *3 1989-90
Y = aEMWT = - 1 . 6 2
bX- 0 . 0 6 * Y E A R
FIGURE 4. Significant linear cooling trend for the Chippewa Lake station(Northeast Division).
The polynomial regression tests (Table 4) also indicatedthat the most recent decades have been cooling. Anegative (i.e., cooling) quadratic polynomial equationcommonly had the best fit for those stations with a longperiod of record. In Table 4, /-test statistics greater than1.96 or less than -I.96 were significant slopes (B) at the95% confidence level (P <0.05). The best fit polynomialwas partly a function of the length of the time series.However, the negative quadratic was the most commonsignificant relationship considering all stations that haveabout a century of EMWT data. Significant polynomialcurves were shown for Wauseon, Canfield, Wooster, andOberlin (Fig. 6) as examples.
DISCUSSIONDescriptive Statistics
The EMWT statistics presented here deviate from theprevious EMWT averages published by Rizzi (1980) andthe handbook of the American Society of Heating,
Refrigeration and Air Conditioning Engineers (A.S.R.A.E.1985) which had only presented 27 Ohio stations forprevious normal periods 1941-1970 and 1951-1980, respec-tively. The average EMWT was approximately 0.5° C to1.5° C colder for most of these stations if the entire climaterecord is considered. A difference of up to 3-2° colderthan the published value (Rizzi 1980) was found for somestations if only the recent normal period was considered.The differences were due to the differences in the normalperiod. This demonstrates the need for updated climaticnormals, and closer scrutiny of previously publishednormals, particularity for extreme values.
For local expectations of EMWT, planners should beaware of the EMWT statistics of the cooperative stationlocated nearest them. Planners are urged to familiarizethemselves with the bias of the cooperative station lo-cated nearest them to compensate for local variability inEMWT. Planners who wish to use plant hardiness zonemaps should be apprised of: 1) the mean EMWT at thestations nearest them, 2) variations resulting from changesin topography over short horizontal differences, and3) any urban bias. Temperatures will tend to be a fewdegrees warmer on clear calm nights on ridges, comparedto the valleys where cold air often accumulates.
The mean EMWT map (Fig. 2) here also varies a fewdegrees Celsius from the Department of Agriculture planthardiness zone map (U.S.D.A. 1990), which used data
D A Y T O N ( C I T Y )
80 90 1900 10 20 30 40 50 60 70 80 1990
WINTERS 1883-84 TO 1989-90
D A Y T O N A I R P O R T
80 90 1900 10 20 30 40 50 60 70 80 1990
WINTERS 1950-51 TO 1989-90
FIGURE 5. Comparison of the time series and linear regression at the A:Dayton city urban site, and the B: Dayton airport rural site (SouthwestDivision).
TE
MP
ER
AT
UR
E
(°C
)
OHIO JOURNAL OF SCIENCE D. G. EDGELL 49
TABLK 3
Linear relationship of extreme minimum winter temperature over time.
NORTHWEST DIVISIONBowling Green Swg PiDefianceFindlay FAA APFindlay Sewage PlantHoytvilleLima Sewage PlantMontpelierNapoleonPandoraPauldingToledo Express APToledo BladeVan WertWauseon Water Plant
NORTH CENTRAL DIVISIONBucyrusElyriaFremontNorwalkOberlinPut-In-Bay Perry MonSanduskyTiffinUpper Sandusky
NORTHEAST DIVISIONAkron-Canton WSO APAshtabulaChardonChippewa LakeCleveland WSO APDorsetHiramMineral Ridge Wtr WksPainesville 4 NWWarren 3 SYoungstown WSO AP
WEST CENTRAL DIVISIONBellefontaine SewageCelina 3 NEGreenville Water PitKentonSidney 1 SUrbana Sewage Plant
CENTRAL DIVISIONCirclevilleColumbus Valley X-ingColumbus WSO APDelawareIrwinLancasterLondon Water WorksMarionMarysvilleNewark Water WorksWesterville
TimeSeries
1894-95ml 894-95
1948-491894-951952-531901-02
ml891-92ml893-94
1949-501935-361954-55
ml870-71ml894-95
1870-71
1894-951949-501952-54
ml894-951884-85
ml921-221883-841886-871882-83
1948-491951-521945-471935-361948-491956-571893-941939-401949-501892-931948-49
1894-951956-571893-941890-91
ml883-841895-96
ml 894-951948-491948-491921-221941-421895-961935-36
ml894-951935-361935-361952-53
Test for Entire Time Series
TV
96774293388988524155369171
120
96413864
10663
107104108
4239455542349751419942
913497
1004495
7442426949895482555537
r2
0.140-0.028-0.2430.020
-0.216-0.1030.0390.120
-0.163-0.300*-0.2310.1120.0590.163
0.030-0.186-0.2060.2360.040
-0.039-0.021-0.1010.096
-0.222-0.373*-0.646*-0.282*-0.296*-0.421*0.083
-0.138-0.188-0.084-0.324*
0.006-0.042-0.1950.0410.123
-0.001
0.021-0.127-0.159-0.219-0.181-0.008-0.131-0.104-0.1230.018
-0.101
Beta
0.018-0.003-0.0440.014
-0.062-0.0140.0130.016
-0.044-0.066-0.0620.0110.0080.020
0.004-0.051-0.0580.0410.005
-0.008-0.002-0.0120.011
-0.071-0.115-0.198-0.058-0.088-0.1140.011
-0.034-0.055-0.012-0.092
0.001-0.015-0.0260.0050.019
-0.000
0.003-0.057-0.041-0.043-0.045-0.001-0.031-0.013-0.0310.005
-0.044
Test HQ
B = 0°
1.373-0.240-1.5660.191
-1.329-0.9690.3310.848
-1.029-2.288*-1.2221.2880.4861.795
0.295-1.182-1.2621.9140.405
-0.303-0.210-1.0220.996
-1.445-2.443*-5.551*-2.141*-1.958*-2.628*0.808
-0.698-1.191-0.850-2.167*
0.061-0.236-1.9400.4020.804
-0.005
0.471-1.016-0.812-1.802-1.259-0.073-1.252-1.013-0.9000.133
-0.598
Test for Normal Period1960-61 to 1989-90
r2
-0.0680.1500.1220.1270.0130.219
-0.005-0.0630.1470.0700.0890.0710.1110.031
0.100-0.0210.060
—0.075
-0.0160.0070.0170.009
0.028-0.151-0.428*0.1670.016
-0.2220.1340.1800.100
-0.0920.019
0.0880.037
-0.0540.166
—0.157
0.0710.1580.0680.079
-0.0290.0600.0990.1870.1080.1330.226
Beta
-0.0260.0590.0460.0490.0050.087
-0.002-0.0250.0560.0280.0310.0300.0430.013
0.038-0.0070.021
—0.029
-0.0070.0030.0060.003
0.013-0.058-0.1720.0530.076
-0.0630.0590.0670.041
-0.0350.007
0.0370.016
-0.0260.070
—0.071
0.0340.0330.0700.037
-0.0120.0280.0420.0700.0490.0580.123
Test HQ
B = 0°
-0.3630.8010.6480.6780.0680.074
-0.028-0.3320.7840.3690.4720.3770.5930.166
0.529-0.1090.314
—0.400
-0.0850.0350.0880.048
0.146-0.810-2.503*0.8970.082
-1.2050.7160.9670.533
-0.4870.100
0.4640.196
-0.2880.888
—0.840
0.3760.3580.8440.417
-0.1550.3180.5271.0090.5770.7081.227
CENTRAL HILLS DIVISIONAshland 2 W ml894-95 84 -0.098 -0.013 -0.886 -0.115 -0.042 -0.615
50 EXTREME MINIMUM WINTER TEMPERATURES IN OHIO VOL. 94
TABLE 3 (Continued)
Linear relationship of extreme minimum winter temperature over time.
CentervilleCharles Mill LakeCoshocton Sewage PitCoshocton Agri RschFredericktown 4 SMansfield WSO APMansfield 5 WWooster Exp Station
NORTHEAST HILLS DIVISIONCadizCanfield 1 SMillport 2 NWNew PhiladelphiaSteubenville
SOUTHWEST DIVISIONChilo Meldahl Lock & DamCin Muni-Lunken FidDaytonDayton WSO APEatonFranklinHillsboroRipley Exp FarmWilmington 3 NXenia 6 SSE
SOUTH CENTRAL DIVISIONGallipolisIronton 1 NEJackson 2 NWPortsmouthWaverly
SOUTHEAST DIVISIONBarnesville-FrdsCaldwell 6 NWCambridge Water PlantMcConnelsville Lock 7New Lexington 2 NWPhilo 3 SWSenecaville LakeTom Jenkins LakeZanesville FAA AP
TimeSeries
1950-511938-391935-361956-571949-501948-491948-491883-84
1903-041916-171921-221960-611941-42
1937-381955-561883-841950-511955-561953-541893-941959-601921-221935-36
1935-36ml882-83
1935-361890-911935-36
1939-40ml935-36ml894-95
1893-941941-421948-491939-40
ml953-541945-46
Test for Entire Time Series
N
39495534413942
107
8773693049
5336
10640353697316955
5510055
10055
504868974942483445
r2
-0.063-0.335*-0.1970.000
-0.243-0.307*0.0930.070
-0.092-0.378*-0.249*0.099
-0.169
-0.073-0.0060.219*
-0.113-0.1970.0070.0740.011
-0.135-0.173
-0.1140.142
-0.179-0.142-0.134
0.212-0.341*0.211
-0.000-0.079-0.251-0.202-0.167-0.099
Beta
-0.021-0.094-0.0540.000
-0.083-0.0930.0290.008
-0.014-0.069-0.0480.041
-0.044
-0.020-0.0020.029
-0.038-0.0910.0030.0110.006
-0.028-0.050
-0.0310.021
-0.057-0.020-0.040
0.006-0.0890.030
-0.000-0.026-0.080-0.067-0.066-0.029
Test Ho
B = 0°
-0.383-2.439*-1.4590.001
-1.340-1.959*0.6310.718
-0.824-3.315*-2.101*0.527
-1.174
-0.970-0.0352.235*
-0.700-1.1600.0400.8180.061
-1.115-1.276
-0.8371.418
-1.327-1.422-0.981
0.147-2.459*1.752
-0.009-0.5460.710
-1.395-0.428-0.264
r2
0.0700.1290.1340.048
-0.113-0.0290.4600.176
-0.0630.1060.1480.0990.035
0.1580.106
-0.0040.011
-0.0790.1150.1770.049
-0.084-0.059
0.075—
0.312-0.1630.201
0.422-0.148
—0.0200.145
-0.0190.023
—0.053
Test for Normal Period1960-61 to 1989-90
Beta
0.0320.0580.0630.021
-0.050-0.0110.1830.066
-0.0280.0370.0640.0410.086
0.0840.059
-0.0020.005
-0.0440.0590.0870.026
-0.043-0.031
0.036—
0.181-0.0870.101
0.187*-0.067
—0.0090.074
-0.0080.014
—0.023
Test Ho
B = 0°
0.3700.6500.7140.252
-0.603-0.1542.742*0.944
-0.3320.5640.7930.5270.186
0.8490.563
-0.0210.058
-0.4200.6150.9490.259
-0.447-0.313
0.400—
1.738-0.8741.083
2.461*-0.793
—0.1060.774
-0.1010.114
—0.280
Time series = Winter the climate record began.N = The number of winters in the climate record.m = At least one missing year in the time series.* = Significant linear relationship (P < 0.05).Test Ho = Test of the null hypothesis that the slope Beta (B) is equal to zero.r2 = Pearson Correlation Coefficient.
from a cooler period of the Ohio climate record (1974-1986). The average EMWTs during the last 30 years arewarmer than that depicted by the U.S.D.A. map. At leastone 30-year period of data should be collected beforeplant hardiness zones are mapped.
Time Series AnalysisThe most recent "normal period" (Table 2) is the coldest
on record for most stations. Most stations in Ohio haveshown either no change over time, or a significant coolingtrend in the most recent decades. The increasing frequency
OHIO JOURNAL OF SCIENCE D. G. EDGELL
TABLE 4
Polynomial regression tests of extreme minimum winter temperature over time.
51
NORTHWEST DIVISIONBowling Green Swg PIDefianceFindlay FAA APFindlay Sewage PlantHoytvilleLima Sewage PlantMontpelierNapoleonPandoraPauldingToledo Express APToledo BladeVan WertWauseon Water Plant
NORTH CENTRAL DIVISIONBucyrusElyriaFremontNorwalkOberlinPut-In-Bay Perry MonSanduskyTiffinUpper Sandusky
NORTHEAST DIVISIONAkron-Canton WSO APAshtabulaChardonChippewa LakeCleveland WSO APDorsetHiramMineral Ridge Wtr WksPainesville 4 NWWarren 3 SYoungstown WSO AP
WEST CENTRAL DIVISIONBellefontaine SewageCelina 3 NEGreenville Water PitKentonSidney 1 SUrbana Sewage Plant
CENTRAL DIVISIONCirclevilleColumbus Valley X-ingColumbus WSO APDelawareIrwinLancasterLondon Water WorksMarionMarysvilleNewark Water WorksWesterville
CENTRAL HILLS DIVISIONAshland 2 WCenterville
RecordStarted
1894-95ml894-95
1948-491894-951952-531901-02
ml891-92ml893-94
1949-501935-361954-55
ml 870-71ml894-95
1870-71
1894-951949-501952-54
ml894-951884-85
ml921-221883-841886-871882-83
1948-491951-521945-471935-361948-491956-571893-941939-401949-501892-931948-49
1894-951956-571893-941890-91
ml883-841895-96
ml894-951948-491948-491921-221941-421895-961935-36
ml894-951935-361935-361952-53
ml894-951950-51
N
96774293388988524155369171
120
96413864
10663
107104108
4239455542349751419842
913497
1004495
7442426949895482555537
8439
X2
-2.001*-2.220*1.590
-1.8711.615
-1.629-3.492*-0.0761.7630.4991.993*
-1.598-1.717-3.042*
-1.5731.1751.527
-1.247-2.870*-1.963*-2.941*-0.780-2.443*
1.0390.7700.2311.1041.3581.978*
-2.102*0.7491.569
-4.214*1.366
-1.5880.464
-2.760*-0.933-2.562*-1.877
-0.8980.7341.024
-0.826-0.043-0.966-0.275-1.8470.5030.4901.735
-3.354*0.358
X 3
-1.0241.406
-0.4660.709
-0.3691.2041.057
-1.026-0.1661.956*
-0.907-1.1190.3870.107
1.2300.124
-1.301-0.560-1.0311.4530.191
-1.484-0.769
0.298-0.2283.142*0.639
-0.2200.7040.8180.9620.5400.3580.170
-0.4320.0050.7860.0140.9120.789
0.385-0.560-0.9750.9300.405
-0.0110.1462.172*0.393
-0.701-1.431
-0.282-0.652
Test for Ho: B= 0
X 4
1.1171.630
-0.2551.3360.3651.3921.7540.147
-0.0480.142
-0.6751.0041.0090.679
1.2000.9210.5060.1982.702*0.3920.2071.6410.728
0.7340.5630.524
-0.1640.1860.7360.004
-0.1250.6972.578*0.613
1.3150.3051.2161.637
-0.7101.402
0.1510.4310.773
-0.454-0.2710.205
-0.0841.0200.2740.3731.555
1.9020.433
X5
0.6440.631
—0.536
—0.7892.098*
-1.073———
1.2320.2190.953
-0.962——
0.2870.853
-0.3061.1720.3281.835
——————
0.927——
1.631—
0.090—
0.8900.6111.353
-0.901
0.315——
-1.065—
0.712—
-0.626——
—
-0.033—
X6
-0.695-0.676
—-1.579
—-1.891-0.1830.574
———
-0.889-1.0670.237
-0.597——
-1.132-2.030*
—-1.382-0.628-1.698
——————
0.231——
-0.345—
-1.135—
0.019-0.722-1.196-0.317
-0.111————
0.987—
-0.539———
-0.163—
X7
———————————
-0.871—
-0.184
——————
-0.182-0.8770.274
—————————1.175—
——————
———————————
——
52 EXTREME MINIMUM WINTER TEMPERATURES IN OHIO VOL. 94
TABLE 4 (Continued)
Polynomial regression tests of extreme minimum winter temperature over time.
Charles Mill LakeCoshocton Sewage PitCoshocton Agri RschFredericktown 4 SMansfield WSO APMansfield 5 WWooster Exp Station
NORTHEAST HILLS DIVISIONCadizCanfield 1 SMillport 2 NWNew PhiladelphiaSteubenville
SOUTHWEST DIVISIONChilo Meldahl Lock & DamCin Muni-Lunken FidDaytonDayton WSO APEatonFranklinHillsboroRipley Exp FarmWilmington 3 NXenia 6 SSE
SOUTH CENTRAL DIVISIONGallipolisIronton 1 NEJackson 2 NWPortsmouthWaverly
SOUTHEAST DIVISIONBarnesville-FrdsCaldwell 6 NWCambridge Water PlantMcConnelsville Lock 7New Lexington 2 NWPhilo 3 SWSenecaville LakeTom Jenkins LakeZanesville FAA AP
RecordStarted
1938-391935-361956-571949-501948-491948-491883-84
1903-041916-171921-221960-611941-42
1937-381955-561883-841950-511955-561953-541893-941959-601921-221935-36
1935-36ml882-83
1935-361890-911935-36
1939-40ml935-36ml894-95
1893-941941-421948-491939-40
ml953-541945-46
N
495534413942
107
8773693049
5335
10640353697316955
5510055
10055
504868974942483445
X2
0.8270.860
-0.3100.6490.6372.087*
-1.285
-1.625-1.9210.354
-0.830-0.254
0.5010.269
-3.447*-0.1430.9010.077
-1.021-0.665-1.214-1.010
-0.178-3.093*1.492
-2.309*0.799
1.592-0.578-2.685*-2.309*0.203
-0.591-0.603-1.6920.432
X 3
0.6740.0840.1981.6950.207
-0.445-1.053
-0.3393.339*0.7481.2441.079
0.327-0.765-0.4500.4510.478
-1.1930.7590.192
-0.2150.381
0.520-1.0640.658
-1.5750.072
0.7170.1140.386
-0.0010.3010.5510.6491.824
-0.272
Test for Ho: B = 0
X 4
0.169-0.4530.6201.7640.078
-0.4002.144*
1.0310.8310.567
—-0.929
0.4610.5470.720
-0.4481.2241.671
-0.3580.9940.8720.097
-0.288-0.997-0.7711.417
-0.750
-0.668-0.1591.4411.424
-0.638—
-0.094—
-0.105
X5
—————
1.009
0.3950.207
-0.640—
—
——
0.864———
0.103—
-0.235—
—-0.720
—-0.857
—
——
-0.8870.219
————
—
X 6
—————
-1.954
-0.393———
—
——
-1.074———
-0.439———
—-1.325
—0.666
—
——
0.9100.561
————
—
X?
—————
0.908
————
—
——
0.906———————
—-0.180
———
————————
—
N = Number of winters in the station record.m = At least one missing year in time series data set.* = Significant polynomial relationship (P <0.05).X2 = Quadratic relationship over time.X^ = Cubic relationship over time.
X^ = Quartic relationship over time.X-1 = Quintic relationship over time.x6 = Sextic relationship over time.X' = Septic relationship over time.H o = Null hypothesis that the relationship is insignificant.
of extremes along the Lake Erie fruit belt (Fig. 3-A) isnoteworthy. Fruit trees need a few years to grow tomaturity. Even if greenhouse warming has contributed toincreased average temperatures, the periodic occurrenceof extreme cold in the life span of fruit trees would stilllimit their distribution. Recent warming during the late1980s world-wide is considered by some climatologists tobe evidence that global warming is well under way.Although the 1980s contain many of the warmest years on
record at stations world-wide (Jones and Henderson-Sellers 1990), some of the coldest EMWTs at several Ohiostations were recorded during that decade (e.g., theSandusky data plot). Perhaps Ohio EMWTs are notbecoming warmer, but more variable.
Data provided by Jones (pers. comm., 1990) showedthat the northern hemisphere warmed at a significantlinear rate; however, the linear correlation and regressiontests (Table 3) showed that Ohio EMWTs are not rising
OHIO JOURNAL OF SCIENCE D. G. EDGELL 53
along with the significant linear hemispheric trend. In fact,in spite of mounting evidence of hemispheric warming(Jones and Henderson-Sellers 1990), Ohio EMWTs haveremained steady or cooled in recent decades. The Daytonstation is an exception, however, since the Dayton EMWTrecord began in 1883-84, the city has grown, and has beenundoubtedly affected by a growing urban heat island. Therural (airport) station at Dayton had an insignificantnegative slope since the EMWT record began in 1950-51.Urbanization has an influence on the time series analysisof temperature data (Jones et al. 1989) reported that urbanbias accounted for a maximum of only 0.1° C change innorthern hemisphere temperatures; however, the differencein EMWT between the two Dayton stations (Fig. 5) is muchmore striking.
The absence of linear significance is likely from thesmall number of short term climate fluctuations in thelonger EMWT series. The stations whose time series beganin the middle portion of the century (1935-36 to 1948-49)commonly had significant cooling trends, however. Thisis explained by the fact that the cool periods of the 1960sand 1970s contrast sharply with the warmer period of the1930s, producing a significant negatively sloped regres-sion line for these shorter-record stations.
Jones and Wigley (1990) had pointed out that themovement of the official weather observations from anurban site to (rural) airport locations may erroneously
indicate a cooling trend. This might explain some coolingtrends at some NWS official "first order" stations. Sincerural areas are cooler, they argue, data from these airportlocations may falsely refute the global warming hypothesis,or at least complicate the trend 0ones and Wigley 1990).This may be true in some areas of the United States andin some other parts of the world, but probably not EMWTsin Ohio. Since Ohio NWS first order station observationshave been changed from cities to airports (1948-49), therehas been a cooling trend for EMWT at most other stationsas well. The (rural) first order stations had cooling trendssimply because these started observations at the begin-ning of the cooling trend. More importantly, it is thecooperative network which supports the conclusion of nosignificant warming. Most cooperative stations were origi-nally located in rural areas unaffected by heat islands, andremain unaffected by urbanization. The Northeast Divi-sion was unique because it has several stations withsignificant cooling trends since mid-century.
If the hemispheric temperatures measured and pre-dicted by other geoscientists increases, a correspondingwarming of Ohio EMWT may not necessarily follow thehemispheric average. Therefore, plants limited in rangeby cold winter temperatures would not be likely to ex-pand their range.
Arguably, there could be a warming of EMWT, but nota linear trend. However, the polynomial regression
W A U S E 0 NQ U A D R A T I C P O L Y N O M I A L
1170 W) 90 1«00
WINTERS 1870-71 TO 1989-90
W 0 0 S T E RQ U A R T I C P O L Y N O M I A L
-10-
-15-
-20-
-25
I
-30-
-35-
- 4 0 -
WINTERS 1883-84 TO 1989-90
-25
-30
C A N F I E L DC U B I C P O L Y N O M I A L
u ~ 2 0
orDi- -25<
a -302
*~ -35
O B E R L I NS E X T I C P O L Y N O M I A L
I1" l"*B70 SO
WINTERS 1884-85 TO 1989-90
WINTERS 1916-17 TO 1989-90
-10
-15
FIGURE 6. Example significant polynomial regression curves. A: Wauseon (Northwest Division) negative quadratic; B: Canfield (Northeast Hills Division),positive cubic; C: Wooster (Central Hills Division) positive quartic; and D: Oberlin (North Central Division) negative sextic.
TE
MP
ER
AT
UR
E
(°C
)
54 EXTREME MINIMUM WINTER TEMPERATURES IN OHIO VOL. 94
analysis also indicated that there has been no overallwarming, although some stations show an upward trendat the end of the eighties (Fig. 6). The negative quadraticpolynomial curve seems to be the best descriptor ofEMWT time series in Ohio. It is debatable whether thedownward bow of the quadratic curve will continue or, ifin the natural course of climatic fluctuations, there will bea trend back to warmer EMWTs.
In Ohio, the past three decades contain a procession ofcooler than average winters during the 1960s, to the warmdecade of the 1980s (Karl et al. 1983). Despite thispotential for a warming of EMWT, there has not been asignificant linear warming of Ohio EMWT. The data fromthe 1980s may indicate that a warming trend is beginning(Jones and Wigley 1990). However, short term fluctua-tions above and below average were common throughthe climate record. (Jones et al. 1982).
A sustained steady rise in EMWT may not endure for atime span of several decades. Perhaps the 1990s willprove to be a warm decade, and perhaps Ohio is due toreturn to the warm temperatures of the 1930s. However,the EMWTs will have to warm several degrees just to attainthe magnitudes reached during that dust bowl decade. Ifthe EMWTs during the 1990s prove to be warmer than the1980s, these temperatures could still be considered wellwithin the range of expectations, considering what EMWThas occurred during the entire climate record in Ohio.
Although there have been relatively warm and coldperiods of EMWT through time, exceptionally coldEMWTs may occur during any winter. The geographicdistributions of plants that are limited by cold EMWT arenot expected to change significantly in the near future, aslong as EMWT remain as cold as they have been in therecent normal periods. Climate change is a complicatedissue however, and these findings of no change in EMWTare not inconsistent with the predictions of some pro-ponents of global warming (Olstead 1993).
In this time of possible global warming and increasingclimatic variability, there is a need for more research onobserved, not speculative or anticipated climate changes.Predictions and models have their place in climatology,yet geographical climatologists should not lose theirunique regional perspectives, and should continue theiranalysis of real world data. There is a need for moreapplied studies (measurable information that has realworld application) that do not subscribe to the globalwarming paradigm. This is an area for the geographicalclimatologists to participate in. Since a political agenda isoften attached to the global warming issue (Riebsame1990), climatologists should remain skeptical about thecauses of global warming or other climate changes as
more regional climate studies are completed. If globalwarming is expected to change temperature or precipita-tion patterns, or initiate more extreme events, then it isup to the geographer to map these real-world observedchanges. The applied climatologist can check local validityof long term predictions. There is a need to examine theactual (measured) climatic response in specific eco-systems. Further studies of extreme values that willinvestigate possible increases in climatic variability aresuggested. Geographical climatology is that part ofclimatology that will measure and assess future globalchanges, and should play a part in long term decisionmaking.
ACKNOWLEDGEMENTS. Appreciation is extended to the National WeatherService personnel and all Cooperative weather observers, past andpresent, whose vigilance has made this study possible.
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