Large ground surface temperature changes of the last three centuries inferred from borehole...

Ž .Global and Planetary Change 20 1999 227–241www.elsevier.comrlocatergloblacha

Large ground surface temperature changes of the last threecenturies inferred from borehole temperatures in the Southern

Canadian Prairies, Saskatchewan

Jacek A. Majorowicz a,), Jan Safanda b, Robert N. Harris c, Walter R. Skinner d

a Northern Geothermal, 105 Carlson Close, Edmonton, Alberta, Canada T6R 2J8b Geophysical Institute, Czech Academy of Sciences, Bocni II, Praha, SporiloÕ, Czech Republic

c Rosentiel School of Marine and Atmospheric Science, UniÕersity of Miami, Miami, FL 33149-1098, USAd Climate Research Branch, EnÕironment Canada, Toronto, Ontario, Canada M3H 5T4

Abstract

New temperature logs in wells located in the grassland ecozone in the Southern Canadian Prairies in Saskatchewan,where surface disturbance is considered minor, show a large curvature in the upper 100 m. The character of this curvature is

Ž .consistent with ground surface temperature GST warming in the 20th century. Repetition of precise temperature logs inŽ .southern Saskatchewan years 1986 and 1997 shows the conductive nature of warming of the subsurface sediments. The

Ž . Ž .magnitude of surface temperature change during that time 11 years is high 0.3–0.48C . To assess the conductive nature oftemperature variations at the grassland surface interface, several precise air and soil temperature time series in the southern

Ž .Canadian Prairies 1965–1995 were analyzed. The combined anomalies correlated at 0.85. Application of the functionalŽ .space inversion FSI technique with the borehole temperature logs and site-specific lithology indicates a warming to date of

approximately 2.58C since a minimum in the late 18th century to mid 19th century. This warming represents an approximateincrease from 48C around 1850 to 6.58C today. The significance of this record is that it suggests almost half of the warmingoccurred prior to 1900, before dramatic build up of atmospheric green house gases. This result correlates well with the proxy

wrecord of climatic change further to the north, beyond the Arctic Circle Overpeck, J., Hughen, K., Hardy, D., Bradley, R.,Case, R., Douglas, M., Finney, B., Gajewski, K., Jacoby, G., Jennings, A., Lamourex, S., Lasca, A., MacDonald, G., Moore,J., Retelle, M., Smith, S., Wolfe, A., Zielinski, G., 1997. Arctic environmental change of the last four centuries, Science

x278, 1251–1256. . q 1999 Elsevier Science B.V. All rights reserved.

Keywords: global warming; geothermics; borehole temperatures

1. Introduction

Simple heat conduction theory predicts that tran-sient temperature changes at the Earth’s surface dif-

) Corresponding author. Fax: q1-403-438-9385; e-mail:[email protected]

fused into the subsurface generate anomalies to thebackground thermal field. The rate of transmission isproportional to the thermal diffusivity, and because

Žthe thermal diffusivity of rocks is low order 1=y6 2 .10 m rs the subsurface contains a thermal mem-

Ž .ory of ground surface temperature GST historiesŽover the last few centuries Cermak, 1971; Jessop,

1990; Pollack and Chapman, 1993; Lachenbruch,

0921-8181r99r$ - see front matter q 1999 Elsevier Science B.V. All rights reserved.Ž .PII: S0921-8181 99 00016-8

( )J.A. Majorowicz et al.rGlobal and Planetary Change 20 1999 227–241228

.1994 . Modelling shows that changes in averagesurface temperatures 10, 100 and 1000 years agoproduce maximum temperature anomalies at depths

Ž .of 25, 80 and 250 m Harris and Chapman, 1997 .Studies of GST warming from the analysis of

temperature–depth logs in wells throughout Alberta,ŽYukon and the Northwest Territories Majorowicz

and Skinner, 1997a,b; Majorowicz and Safanda,.1998 indicate warming of about 28C over the last

century. However, linear trends fit to surface airŽ .temperature SAT data for the Northwestern Forest

Žand Canadian Prairie climate regions Environment.Canada SOE Report, 1995 indicate only 1.48C and

0.98C, respectively, over a roughly similar time pe-riod. The difference in warming magnitudes is espe-cially strong in areas where land clearing due to

Ž .either natural causes forest fires or anthropogenicŽ .causes deforestation and farming caused increasing

Žsolar heating of the ground Majorowicz and Skin-.ner, 1998 . Land clearing for farming has been in

effect in Alberta since the early part of the 20thŽ .century. Majorowicz and Skinner 1997a showed

that differences between ground surface warming atthe well sites and surface air temperature warming atthe climatic stations are large in the boreal forest

Ž .ecozone northern Alberta , whereas they are smallor non existent for southern Alberta in the grasslandecozone. The latter comparison has been limited tothe last half a century due to a lack of numerous

Ž .deep wells deeper than 120 m . This reduced warm-ing rate observed in SATs relative to the GSTs may

suggest that SATs would have warmed even less hadŽthe ground cover not been disturbed Majorowicz

.and Skinner, 1997b .The new data south of the Canadian border in the

Dakotas and Nebraska show large GST warmingmagnitudes exceeding SAT warming for the last 100

Ž .years Gosnold et al., 1997 . GST histories derivedfrom the recent well temperature data farther east, in

Ž .Manitoba, Canada Guillou-Frottier et al., 1998 fol-Žlow the same trend as that of weather stations ap-

.proximately 28C warming of the last 150 years .This paper presents new borehole temperature–

depth logs measured primarily in the years 1995–1997, from the grassland ecozone of Saskatchewan.Repeated precise temperature measurements in 1997in four wells near Riverhurst in Saskatchewan pro-vide a good test of the warming source. After aninterpretation is made of the temperature–depth data,our models are compared to SAT data from theobservations in the Environment Canada stations.The latter record is mostly limited to the time framefrom 1895 to the present. Temperature–depth dataprovide information on the mean surface temperaturepreceding the SAT data and provide a longer termperspective on magnitudes of contemporary warmingŽ .Deming, 1995; Harris and Chapman, 1997 .

2. Temperature logs

Temperature–depth logs were measured in 10wells throughout southern Saskatchewan in areas of

Table 1Ž .Description of the well sites together with the year of the reconstructed GST minimum and the amplitude DT of the consequent warming

as based on ‘loose inversions’ of temperature logs

No. Well Lat. deg. N Long. deg. W Logged year Terraine Minimum DT

year 8C

1 TS941 54.45 109.87 1994 clearcut 1850 1.82 T965 53.06 103.95 1996 crop field ? 1.53 T964 52.26 105.52 1996 grass 1890 2.94 T966 52.02 107.12 1996 grass 1840 2.65 T967 52.01 107.11 1996 grass 1870 2.76 Riverhurst9c 50.948 106.997 1997 grass 1870 2.07 Riverhurst1c 50.921 106.957 1997 grass 1870 2.88 Riverhurst5b 50.899 106.907 1997 grass 1820 2.59 Riverhurst8c 50.879 106.867 1997 grass 1870 2.1

10 TKT1 49.07 106.25 1994 grass 1890 2.5

( )J.A. Majorowicz et al.rGlobal and Planetary Change 20 1999 227–241 229

mainly grass, and in one case by crop cover. Thelocations of the well sites, time of measurement, typeof terrain, depth interval and magnitude of warming

Ž . Žbased on the functional space inversion FSI , Shen.et al., 1995a,b; Majorowicz and Safanda, 1998 are

shown in Table 1. Fig. 1 shows the locations of the

sites in this study, and others from midwestern NorthAmerica published to date. The Saskatchewan datafill the gap between the measurements from the

ŽGreat Plains of U.S. Deming, 1995; Gosnold et al.,.1997 and the measurements in the Aspen Parkland

Žand Boreal Forest of Alberta, Canada Majorowicz

Fig. 1. Study area of South Saskatchewan and of well sites with temperature logs used for study of climatic change in mid and northAmerica.


.and Safanda, 1998 . The logs were done with onetype of equipment which consisted of a thermistorprobe, bridge and cable. The calibration of the ther-mistors was done in the Geothermal Lab of the Earth

Ž .Physics Branch Geological Survey . Instrumentalprecision of temperature measurements is better than0.018C. The wells were undisturbed for at least 5

Ž .years 11 years in the case of Riverhurst wells .Therefore the influence of drilling disturbance isconsidered minimal. The logs are shown in Fig. 2.

The most interesting are repeated temperature logsŽin the four wells of the Riverhurst area sites—1c,

.5b, 8c, 9c . First temperature logs were done inSeptember of 1986 under contract from theSaskatchewan Research Council under the supervi-sion of Dr. Jessop of the Geothermal Lab of the

ŽEarth Physics Branch now Geological Survey of.Canada . The temperature logs were repeated in

these wells by the first author in four wells availableŽ .for measurements in June 1997 sites 1c, 5b, 9c and

Ž .in September 1997 site 8c . The wells in the River-hurst area had also a detailed lithology description

Ž .and gamma ray and electrical logs SP, Resistivitywhich helped in estimation of thermal conductivityand construction of the layered model.

The new and old Riverhurst temperature profilesare shown in Fig. 3. The difference between 1997logs and 1986 logs is 0.48C at the shallowest depths.At depths greater than 100 m the agreement between1997 and 1986 is close, however the difference in

Fig. 2. Temperature logs in South Saskatchewan.

calibration between 1997 and 1986 log caused theaverage difference at the 140–240 m interval to be

Ž .q0.0378C Fig. 4 . We have adjusted the 1986 logsby this average difference before the inversions.

3. Surface air temperature warming vs. soil tem-perature variations

Comparing soil temperature time series with airtemperatures measured at the screen level for thesame locations and corresponding time intervals is agood way of testing if the temperatures track oneanother. Since inversion of the temperature profilesgives the ground surface temperature history, thecorrespondence of soil temperature changes to airtemperature changes is critical. Such tests wereshown to give positive results in the case of theUniversity of Minesota St. Paul campus climatologi-

Ž .cal observatory Baker and Rushy, 1993 with soiltemperatures closely tracking the surface air temper-atures. Another study that use NOAA operated sta-tions in the High Plains Climate Center Network inU.S.A. did not find close correspondence of soil and

Žsurface temperatures Gosnold et al., 1997 and Gos-.nold, 1998, private communication . Gosnold et al.

Ž .1997 interpret this discrepancy to be a result ofincrease in precipitation during the past 50 years inthe area causing air and soil temperatures to divergeduring the freezing season. In our study area, precipi-tation in the grassland prairie averages less than 500mmryear and shows no significant change during

Žthe last 100 years Environment Canada SOE Report,.1995 .

In our study area, daily soil temperature data, at10 cm depth below the surface for the period 1965–1995, were obtained from Atmospheric Environment

Ž .Service AES and Canadian Department of Agricul-Ž .ture CDA weather stations. The prairie grassland

ecozone stations were: Swift Current, Edson, Vaux-hall, Lethbridge, University of Calgary, Lacombe,Ellerslie, and Vegreville. The boreal forest ecozonestations were: Fort Vermilion, Peace River, SlaveLake, Beaverlodge, and Wagner. Surface air temper-

Ž .ature SAT warming trends were based on the abovestations and also upon stations taken from the Histor-

Žical Canadian Climate Data base Skinner and Gul-.let, 1993 .


Ž . Ž .Fig. 3. Temperature logs 1997 logs vs. 1986 logs in four wells of the Riverhurst South Saskatchewan area.

Ž .The two graphs Fig. 5a,b show soil temperaturechanges and the air temperature changes for borealand prairie ecozones, respectively, for the 1965–1995period. The short common reference period of 1973–1981, used for anomaly calculations for both air andsoil temperatures, is limited by the soil data avail-ability at many sites. The soil data had some gaps.However the large amount of stations used allowedobtaining quite accurate soil warming anomaly varia-tions. The soil curves correlate significantly with the

Ž .corresponding air curves Rs0.85 for the grass-land. For the boreal forest which is mostly north ofthe study area, the correlation coefficient is only

0.56. The reasons for the greater consistency be-tween SAT and GST in the grassland as compared tothe boreal ecozones are not exactly known. It mightbe connected to a relatively greater similarity be-tween pre-settlement and modified surface condi-tions in the grassland part of the Canadian PrairiesŽ .Majorowicz and Skinner, 1997b . There is also adifference in the moisture patterns between the eco-

Žzones. Dry conditions of the southern Prairies En-.vironment Canada SOE Report, 1995 can be the

other reason for closer tracking between GST andSAT time series. In any case, the high correlationcoefficient obtained for the grassland stations adds


ŽFig. 4. Difference temperature logs 1997ytemperature logs.1986 .

confidence to our evaluation of climatic warmingfrom the analysis of the temperature logs.

4. Inversion of temperature profiles

Ž .Application of the functional space inversion FSIŽ .technique of Shen et al. 1995a,b was used to

Ž .calculate of the ground surface temperature GSTŽ .histories from temperature profiles Table 1 . Pollack

Ž .et al. 1996 have analysed the problem of random orsystematic noise in the temperature vs. depth data

Ž .and its influence on the inferred GST history GSTHusing inversion techniques. The limitations of themethod are related to our knowledge of precisetemperature–depth profile, of conductivity and 3Dstructure. The inversion approach was also used inderiving GST histories for Alberta and northern

ŽCanadian temperature profiles Majorowicz and.Safanda, 1998 . Due to limited information on the

geophysical rock properties, the conductivity wasestimated from the general description of the lithol-ogy type and known average conductivity of the

Žmain rock type in the Williston basin Jessop and.Vigrass, 1989; Gosnold et al., 1997 . At first the

average conductivity of the shallow lithology profilein the wells of the study area was estimated to be 1.6

y1 ŽW mK mostly controlled by the low assumedŽ y1 ..conductivity of shales 1.2 W mK . In the case of

the Riverhurst area wells information from geophysi-

cal logs and detailed net rock data allowed construc-Ž .tion of the conductivity profiles with depth Fig. 8 .

The a priori conductivity of 1.6 W mKy1 and ther-mal capacity of 2=10y6 J Ky1 sy1 were assumed atfirst. Heat generation of 2=10y6 W my3 wasassumed. However, the model of heat productioninfluences the results very little and is practicallyunresolved by the inversion. We have assumed theheat transfer to be by conduction alone through aone-dimensional, possibly heterogeneous medium.

Ž .In the ‘loose inversion’ Shen et al., 1995a partof the information is attenuated to ensure that noiseis not amplified. This suppression of the noise wasachieved by increasing the standard deviation of thea priori thermal conductivity model and the standarddeviation of the measured temperatures. Threeversions were considered, one with a priori conduc-tivity and temperature standard deviation of 0.5 WmKy1 and 0.058C, respectively, the other two with

ŽFig. 5. Anomalies of the mean annual temperature time series soil. Ž .temperatures and air temperatures at the screen level . a Boreal

Ž .forest ecozone, b Grassland area of the Canadian Prairies.


2 W mKy1 and 0.058C and 4 W mKy1 and 0.18C.Ž y1 . ŽThe combination 4 W mK , 0.1 K and 2 W

y1 .mK , 0.05 K represents a higher uncertainty in thea priori information, and compared to the combina-

Ž y1 .tion 0.5 W mK , 0.05 K , the inversion explains ina greater degree the measured temperature profile bychanges in the a priori conductivity model and doesnot strictly insist on the exact reproduction of themeasured profile by the a posteriori model of the

Ž .GST history GSTH and thermophysical parameters.Ž y1In the case of our data the combination 2 W mK ,

.0.058C gives quite consistent GSTH throughout thearea. Fig. 6 shows an example of such ‘loose’ inver-sion for the site T964 which is characteristic for allŽ .see Table 1 for location . It is typical to see temper-ature warming starting at the turn of the century or adecade or two prior to that, a recovery from thecolder period. The magnitude of warming is large

Ž .and varies between 1.58C and 2.98C T964 .The logs from sites 1c, 5b, 8c and 9c were also

Ž .processed FSI inversions using depth dependentŽ .conductivity models Fig. 8 . The first change with

the lithology adapted conductivity is the decrease ofthe diffusivity. Whereas the homogeneous modelshad diffusivity 0.8=10y6 m2 sy1 the depth conduc-tivity models have diffusivity 0.625, 0.665, 0.640

Ž y6 2 y1.and 0.625 =10 m s , respectively, becausethe weighted averages of conductivity are lower andthe assumed specific heat has not been changed. Theeffect of lower diffusivity is demonstrated in Fig. 7awhere the inverted GST histories for models with

Fig. 6. Example of ‘loose’ inversion using method of Shen et al,Ž .1995a,b for the case of temperature log in well T964 Table 1,

Ž y1 . Žcurves 1–3 represent the versions 0.5 W mK , 0.05 K , 2 Wy1 . Ž y1 .mK , 0.05 K and 4 W mK , 0.10 K respectively.

Ž .Fig. 7. a–c Illustration of the effect of different conductivitymodels and a priori constrains upon conductivity and temperature

Ž .on the derived GST history well Riverhurst 1c .

Ž y1 .diffusivity 0.8 curve 1—conductivity 1.6 W mKŽand diffusivity 0.625 curve 2—conductivity 1.25 W

y1 .mK are shown for the 1997 log from borehole 1cŽ Ž y1 ..version with a priori S.D. 0.5 W mK , 0.058C .


The local GST maximum in the 19th century isshifted for the lower diffusivity model by 15–20years toward the past. The effect of the averagediffusivity decrease is, however, of minor impor-tance in comparison with the effect of the depthvariation of the conductivity. The new a priori depthdependent conductivity model changes substantiallythe reconstructed GST history. This is illustrated inFig. 7a by curve 3. The 19th century maximum hasdisappeared completely and was replaced by theshallow minimum, centred at the middle of the last

century. The effect of the depth dependent conduc-tivity for the other versions of a priori S.D.’s isshown in Fig. 7b–c. For corresponding version of

Žhigher a priori S.D. of conductivity 2.0 and 4.0 Wy1 .mK , the course of the reconstructed GST histo-

ries is similar, but the amplitude of the recent warm-ing is slightly higher for the depth dependent con-ductivity model.

The main source of differences between the GSThistories yielded by borehole 1c for constant anddepth dependent a priori conductivity models for

ŽFig. 8. Thermal conductivity models and corresponding thermal gradients based on temperature logs from wells in the Riverhurst area 1c,.5b, 9c, 8c respectively.


ŽFig. 9. Comparison of a priori constant average thermal conduc-.tivity conductivity model and a posteriori model for Riverhurst

1c.

Ž y1 .version 0.5 W mK , 0.058C is the local maximumof the temperature gradient in the depth interval

Ž .80–100 m Fig. 8a followed by 25% decrease. EvenŽmore pronounced is this feature in borehole 9c Fig.

.8c , where the difference between the value of thegradient maximum centred at a depth of 100 m andthe adjacent minimum in 120–130 m amounts to40%. If not compensated by conductivity, this ‘bulge’

Ž .Fig. 10. Comparison of a priori lithology adapted conductivityconductivity model and a posteriori model for Riverhurst 1c.

of temperature log is interpreted by the inversionalgorithm as a transient feature caused by GSTwarming in the 19th century. The conductivity mod-els derived from the lithological profiles by assign-ing the typical conductivity values to the individuallithological units for borehole 1c, 5b ,8c and 9c areshown in Fig. 8a–d, respectively. The maxima of thethermal gradient are lithology related. The gradient iscorrelated with the conductivity models also in theother sections of the boreholes below 100 m.

Fig. 11. a–b. The difference of a posteriori–a priori temperatureŽ .profile for the case of homogeneous conductivity model a and

Ž .lithology adapted conductivity model b .


The a priori and a posteriori conductivity profilesfor the constant and depth dependent models aregiven in Figs. 9–10, respectively, for log 1c—1997.A posteriori conductivity-versus-depth curves of thehomogenous model have a tendency to compensatethe gradient maximum at 80–100 m by a conductiv-ity increase below this depth, but for the small S.D.’sof a priori conductivity model, 0.5 or 1.0 W mKy1,the compensation is insufficient.

The differences of a posteriori–a priori tempera-ture profiles for homogeneous and depth dependentmodels are shown in Fig. 11a–b respectively. Thedegree of agreement between a posteriori and apriori temperature vs. depth profiles is slightly better

Žfor the depth dependent model S.D. of the differ-. Žence 0.0098C than for the homogeneous one S.D.

.0.0108C .The conductivity models derived from the litho-

logical profiles approximate well the real conditionsŽ .in all four cases 1c, 5b, 8c, 9c . For this reason the

inversions were carried only for the lower a prioriS.D.’s of conductivity, namely 0.5 and 1.0 W mKy1.The inversions are shown in Fig. 12a–b. The resultsare summarised in Fig. 13 as the arithmetical averageof the individual GST histories obtained from bore-holes 1c, 5b, 8c and 9c by the simultaneous inver-sions of the 1986 and 1997 logs. The GST historieswere shifted to 08C for the year 1700. The average

Fig. 12. GST histories from inversion of temperature logs based on lithology adapted conductivity model for 1986 and 1997 logs andsimultaneously 1986 and 1997 for wells in Riverhurst area: 1c, 5b , 8c, 9c.


Ž .Fig. 12 continued .

warming is 2.58C starting at the minimum approxi-mately 1820"50 years. This is some 1.28C higherthan the SAT warming based on statistical approxi-mation by linear function of the time series from the

Ž .AES stations Environment Canada, 1996 for thelast 100 years.

5. Baseline temperatures for 20th century warm-ing

We have shown from the SAT and soil tempera-ture data set that soil temperature time series and air

surface temperatures correspond for the study area ofŽthe southern Saskatchewan grassland the so called

.Palliser Triangle area . To get a sense of how wellthe FSI solutions correspond to SAT measurementsfrom nearby meteorological stations, we average themeteorological stations from the southern grassland

Ž .ecozone Saskatoon and Riverhurst with the averageFSI results from wells 1c, 5b, 8c, and 9c in theRiverhurst area. The average SAT time series isshown in Fig. 14a. A linear fit to the SAT dataindicates warming of about 1.48Cr100 year. Theaverage transient temperature–depth profile is shown

Ž .in Fig. 14b dots . Because the solid Earth is a low


Fig. 13. Arithmetic average of the individual GST histories frominversions of temperature logs in Riverhurst wells.

pass filter to surface temperature variations, GSTcurves represent a smeared but robust average of theactual GST history.

A temperature–time point on the GST curve rep-resents a robust temperature average over a timewindow that expands as we look farther into the pastŽ .Clow, 1992 . High frequency variations present inSAT time series are diffused away due to both thephysics of the problem and the size of the a prioristandard deviations used during the inversion. Incontrast, SAT time series represent discrete annualmeans that do not suffer from a loss of frequencycontent as we look back in time, but only extendback to circa 1900. We use the SAT time series as aboundary condition for the function at the Earth’ssurface and calculate a synthetic transient using afilter representing the conductive Earth. This proce-

Ždure is described by Harris and Chapman 1997,.1998 , based on concepts laid out by Lachenbruch et

Ž .al. 1988 . We parameterize the SAT data in terms ofa series of N step functions of amplitude DT andi

time prior to the borehole temperature measurementŽ .t Carslaw and Jaeger, 1959 :i

N

T z s DT erfc zr 4a t 1Ž . Ž .(Ý ž /r i iis1

where erfc is the complementary error function anda is thermal diffusivity. This calculation depends onan assumption and one free parameter. The offset

between air and ground temperatures must be re-moved and because of a lack of information to thecontrary, we necessarily assume that the offset isconstant through time.

To keep the model as simple as possible weinitialize the time prior to the advent of the SATmeasurements in terms of a preobservational mean

Ž . Ž .temperature POM , so that DT s T yPOM . The1 1

POM is the only free parameter. In practice the POMis determined by finding the value that minimizes themisfit between the transient temperatures and thosegenerated from the SAT data. For this data set thePOM is given relative to the mean SAT. The com-parison between the average transient profile and

ŽSAT–POM model is shown in Fig. 14b dashed.line . Fig. 14c shows the misfit at a scale about 10

times larger. In general this simple one parametermodel explains about 84% of the transient. Whilethese models explain most of the transient tempera-tures, the differences between the transients andsynthetic temperature–depth profiles show the pres-ence of a systematic trend not explained by the SAT

Ž .time series Fig. 14c . The long wavelength shape ofthe misfit profile can be understood in terms of a

Ž .boxcar function Fig. 15 . The average time of theboxcar event, t , can be related to the depth of thea

maximum anomalous temperature z , through themŽ .equation Lachenbruch, 1994 :

t sz 2 r2a 2Ž .a m

where a is thermal diffusivity. This is the averagethermal length based on the two steps comprising theboxcar. In this case the average time of the boxcarŽ .circa 1830 precedes the start of the average SAT

Ž . Ž .time series 1902 , Table 2 leading us to hypothe-size that the misfit might be due to a cool intervalpreceding the SAT time series. We assume that theyear of the first annual mean temperature of the SATtime series is a good approximation to time t and1

solve for t . The maximum anomalous temperature2

T and the duration of the event DT can be related tom

the product H=DT ,

Hs4T t rDT 3Ž .m a

Using only one iteration, these corrections showremarkable improvement in the RMS misfit, a factor

Ž .of about 3 solid lines, Fig. 14b and c . Combining a


Ž .Fig. 14. Comparison between average SAT time series and average transient temperature–depth profile. a SAT time series based onŽ . Ž .Regina and Saskatoon, and boxcar model. b Transient temperature–depth profiles. Average transient temperature–depth profile dots ,

Ž . Ž . Ž .POM–SAT model dashed line , and boxcar–SAT model solid line . c Temperature misfits. Difference between average transientŽ . Ž .temperature–depth profile and POM–SAT model dashed line and boxcar–SAT model solid line .

boxcar preceding the SAT time series with thePOM–SAT model now explains 95% of the data.

The agreement between these simple models con-structed using the SAT time series as its basis and


Ž .Fig. 15. Conceptual model of temperature–depth response a dueŽ . Ž .to surface temperature change in the past ‘boxcar event’ b , H

is the magnitude of the surface temperature change of the durationt y t ; T is the resulting temperature vs. depth anomaly.2 1 m

the average transient temperature–depth profile isremarkable. Using only one free parameter we areable to explain most of the data. These modelssuggests that the borehole temperatures and SATsare being influenced by the same driving forces.Additionally, the most significant disagreement be-tween the simple POM–SAT model predates thestart of the SAT time series, and indicates that thecool interval inferred from the FSI analysis is resolv-able. The smaller temperature misfits at 40 m depthand corresponding time period centred around 1955could be a result of the transient effect or show thatthe improvements and refining of the conductivitymodel would be needed. Obviously there is a dangerof overinterpreting these misfits.

6. Conclusions

Both modelling of the GST history from geother-mal data using the FSI method only and using acombination of geothermal data and SAT time seriesindicate that a cool period existed in the 18th–19thcentury prior to the present century’s warming. Thefirst method indicates that in the recent decades ofthis century the GST warming is larger than SATwarming. There is no significant change in precipita-tion in the southern Canadian Prairies during last 100

Ž .years Environment Canada SOE Report, 1995 ,which may have offered some explanation as to whythe GST is warming faster than SAT in the recentdecades. The large magnitude GST warming may bevery real and related to the combined environmentalchange which would include changing land surfaceŽ .Majorowicz and Skinner, 1997b . SAT warming isinfluenced by the GSTs, so that SATs show morewarming than would be observed under undisturbedconditions.

In the second method comparison of the transienttemperature–depth profiles and the SAT time seriesfor the study area shows that the SAT record is notlong enough to sufficiently judge contemporarywarming trends. In fact, the magnitude of warming issignificantly higher when the GST history is ana-lyzed for the whole length of the recent 3 centuries.Warming may have been as high as 38C between the18th–19th century and present.

Further, it is significant that the level of GSTtemperatures before 1900 was about y1.28C lowerthan the mean surface air temperature level. The datashown in this paper and results from both sets ofmodelling procedures imply that the last majorwarming event began in the 18th–19th century. Thesignificance of this record is that it suggests almosthalf of the warming occurred prior to 1900, beforedramatic build up of atmospheric green house gases.This result correlates well with the proxy record of

Table 2Model parameters

Ž . Ž . Ž . Ž . Ž . Ž .Metheorological stationryear z m T 8C t ybp t ybp H 8C POM 8C RMSm m a 2

Ž . Ž .Averages 80 0.15 164 1833 232 1765 0.7 y1.2 17


climatic change further to the north, beyond theŽ .Arctic Circle Overpeck et al., 1997 .

Acknowledgements

We gratefully acknowledge helpful comments ona previous version of this paper by three anonymousreviewers. Support for this work came in large part

Žfrom Environment Canada Climate Research.Branch, CCRD . IGCP 428 project financing helped

ŽJ.A.M. to attend the meeting at Moscow Interna-.tional Geothermal Conference to present the basic

ideas covered by this paper. We thank Ed Jaworskiand Dennis Zlipko of the Saskatchewan ResearchCouncil for arranging the access to the well sites andfor valuable geological and hydrological information.

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