Evidence of climate warming from underground temperatures in NW Italy

www.elsevier.com/locate/gloplacha

Global and Planetary Cha

Temperature signal in the underground for climate history

reconstruction in Italy

V. Pasqualea,*, M. Verdoyaa, P. Chiozzia, L. Bodrib, S. Bellanic

aDipartimento per lo Studio del Territorio e delle Sue Risorse, Universita di Genova Viale Benedetto XV 5, I-16132 Genoa, ItalybGeophys. Res. Group, Hung. Acad. Sci., 1083 Budapest, Hungary

cCNR, Istituto Geoscienze e Georisorse Via Moruzzi 1, I-56124- Pisa, Italy

Received 22 December 2003; accepted 30 November 2004

Abstract

Underground temperature data from height boreholes logged between 1981 and 2000 were studied to infer the climate

change in central-northern Italy during the last 250 years. The ground surface temperature history was reconstructed by using

the functional space inversion method. A different inverse approach was also used for two temperature sets to obtain the fine

details of the most recent surface temperature change. The results were compared with the air temperature recorded since the

beginning of the 19th century at meteorological observatories. The analysis puts into evidence that the trend of the temperature

change in the western side of the Apennines chain differs from that of the eastern side. Since 1750 the western side shows

temperature lower than that of the 1990s, with minimum values in the period 1930–1960, followed by an almost linear increase

in the ground surface temperature. Along the eastern side the temperature is always larger than that inferred for the 1970s, with

maximum values in the period 1920–1940, which is followed by a sharp temperature decrease. Only since 1970–1980 a local

warming phase has started. By combining borehole temperature logs with meteorological surface air temperature records, the

pre-observational mean temperature was calculated. The results corroborate the difference of the climatic histories in both sides

of the Apennines concerning the ground surface temperatures. It also appears that the recent climatic changes have partly a local

origin and can obscure the changes forced by the regional surface air temperature influence.

D 2004 Elsevier B.V. All rights reserved.

Keywords: climate change; meteorological record; ground temperature history; global warming, Italy

1. Introduction

Analyses of surface air temperature (SAT) time

series, recorded over the period 1867–1995 at a

0921-8181/$ - see front matter D 2004 Elsevier B.V. All rights reserved.

doi:10.1016/j.gloplacha.2004.11.015

* Corresponding author. Fax: +39 10 352169.

E-mail address: [email protected] (V. Pasquale).

number of meteorological stations scattered on the

whole Italian territory, roughly delineated two

climatic sub-regions, northern and central-southern

Italy, both revealing increase in the temperatures

with average rates of 0.3–0.4 and 0.5–0.7 K/100

year, respectively (Maugeri and Nanni, 1998; Bru-

netti et al., 2000). These values are somewhat lower

nge 47 (2005) 36–50

V. Pasquale et al. / Global and Planetary Change 47 (2005) 36–50 37

to the north and coincide well to the south with the

estimates by Ghil and Vautard (1991) and Jones

et al. (1999) for the Northern Hemisphere. However,

the Italian orography and the position of the country

surrounded by the Mediterranean Sea imply strong

effects of the local air circulation that cause high

spatial and temporal climate variability (Pasquale

et al., 1996; Nanni et al., 1998).

To identify these differences by using only

meteorological data is problematic because of the

relative raw spatial resolution of the existing SAT

records and the possible presence of hidden inhomo-

geneities. Information from independent sources must

be considered to obtain more details on the climatic

pattern. The surface temperature changes inferred

from the inversion of underground temperature

measurements can supply an additional record of the

past climate signal. Pasquale et al. (1998, 2000) have

recently tested the applicability for northwestern Italy

of methods that utilise borehole temperature data to

infer the climatic history where meteorological data

are not available. On the basis of thermal information

from a selected geothermal borehole, they recon-

structed the climatic history since 1700, by employing

both inversion techniques and a forward modelling,

which combines air temperature time series from

conventional meteorological observatories with bore-

hole temperature profiles. The temperature signal

prior to the 1830s indicates a slightly warmer climate

compared to that of the 1990s and a sensibly

temperature rise during the last decade.

In this paper, we try to extend such an analysis to

outline the pattern of the recent climatic history at the

regional scale by studying the climatic signal stored in

geothermal boreholes scattered in central-northern

Italy. Inverse methods are used to infer the ground

surface temperature (GST) history from underground

temperatures recorded during the last 20 years, which

were partly available from the literature and partly

measured especially for this study. In particular, two

new datasets recorded in 1999–2000 are presented

together with results of thermal conductivity measure-

ments on borehole core samples.

Moreover, borehole temperature profiles were

combined with SAT records to obtain a baseline

temperature before the 19th century. Such linking

can give more reliable inferences about past temper-

ature variations than the meteorological time series

alone and can help to distinguish whether the

recently observed warming represents a natural

climatic variation or an induced anthropogenic

change of climate.

2. Underground temperatures

A number of boreholes have been drilled in the

last 20 years for surface heat-flux studies and

exploration of geothermal resources in central-north-

ern Italy. Underground temperatures can be affected

in principle by several kinds of thermal perturba-

tions, which deviates their shapes from that expected

for pure conduction heat transfer. Among the

available data, we have chosen only those temper-

ature–depth curves showing no or negligible thermal

perturbation, caused by groundwater circulation. The

selected dataset consists of eight temperature–depth

profiles, four of which were recorded in boreholes

located in the Tyrrhenian side of the Alps–Apennines

system and four in the Adriatic side (Fig. 1). The

boreholes are located in areas with subdued topog-

raphy and small elevation variations within a radius

of few kilometres, and are free of potential disturb-

ing effects of water masses. Their geographic

coordinates and logging time are shown in Table 1

while the temperature–depth distribution is shown in

Fig. 2.

2.1. Available data

Data of underground temperatures and thermal

conductivities for the borehole GH1, located in the

Tyrrhenian side of the northern Apennines, were

taken from a study by Verdoya et al. (1999). No

significant lithological variation exists along the

whole borehole, which is characterized by alternate

clay and marl. The recorded temperature profile

points to water flow in the 125–175 m depth range,

due to the presence of thin permeable layers. This

produced a slight perturbation on the background

thermal gradient. The temperature profile shown in

Fig. 2 includes a small correction within the

perturbed depth range, calculated according to the

approach of Ramey (1962). Laboratory results of

thermal conductivity measurements are available for

five marl samples collected near the borehole and

Fig. 1. Shaded relief map of central-northern Italy and location of the boreholes and the Meteorological Observatories whose thermal data were

used for the climatic study.

V. Pasquale et al. / Global and Planetary Change 47 (2005) 36–5038

four core specimens selected from the depth intervals

between 150 and 200 m. An average value of

2.2F0.1 W m�1 K�1 was determined (Chiozzi et al.,

1998).

Table 1

List of the investigated boreholes together with year of the

temperature measurements

Site Well Year Lat. N Long. E Alt.

(m)

Depth

(m)

Ref.a

Acqui Terme GH1 1996 448 40.6V 088 27.2V 152 200 1

Torniella GH2 1993 438 04.4V 118 11.6V 350 145 2

Fontalcinaldo GH3 2000 438 07.0V 118 29.4V 720 358 3

Murci GH4 1999 428 45.3V 118 24.3V 380 200 3

Imola GH5 1982 448 19.4V 118 38.1V 78 150 4

S. Marino GH6 1982 438 58.1V 128 28.2V 110 200 4

Rapagnano GH7 1981 438 10.1V 138 36.0V 120 190 4

Giulianova GH8 1982 428 42.5V 138 51.8V 105 200 4

a 1, Verdoya et al. (1999); 2, Baldi et al. (1994); 3, this paper; 4,

Mongelli and Zito (1988).

The lithological sequence observed in the bore-

hole GH2, located in the Tyrrhenian side south of

Florence, primarily consists of shales, and seconda-

rily of marly limestones and limestones both in the

uppermost 40 m and below 105 m. The rest of the

stratigraphy is characterized by prevailing limestones

and marly limestones, with minor layers of shales.

Several samples were collected for thermal conduc-

tivity determinations, and the resulting geometric

mean value is 2.2F0.2 W m�1 K�1 (Baldi et al.,

1994).

Boreholes located in the Adriatic side (GH5–GH8)

were drilled into clayey formations and the measured

underground temperatures showed that they were not

affected by relevant non-conductive disturbances

(Mongelli and Zito, 1988). The section consists of

clays and sandy clays in borehole GH5, located to the

south of Bologna, with the mean thermal conductivity

value of 1.8F0.3 W m�1 K�1. The hole GH6 is 200 m

Fig. 2. Temperature–depth distribution in the boreholes whose location is shown in Fig. 1.


deep. It crossed marly clays with silt intercalating very

thin sandy levels. Thermal conductivity determined

for core samples selected at 30–35 m one from each

other is 1.4F0.1 W m�1 K�1.

The boreholes GH7 and GH8 are located south of

Ancona. GH7 crossed silty clays down to 75 m and

subsequently sandy clays down to the bottom at 190

m. The hole GH8 has uniform lithology, consisting of

silty clays, excepting a thin lens of conglomerate at

the depth of 94 m. The mean thermal conductivity

determined on cores recovered every 25–30 m for the

Table 2

Underground temperatures observed in the borehole GH3

Depth (m) Temperature (8C) Depth (m) Temperature (8C) D

30 11.99 115 16.69 2

35 12.23 120 16.96 2

40 12.44 125 17.29 2

45 12.67 130 17.60 2

50 12.89 135 17.88 2

55 13.15 140 18.14 2

60 13.45 145 18.42 2

65 13.57 150 18.67 2

70 13.89 155 18.89 2

75 14.21 160 19.28 2

80 14.53 165 19.58 2

85 14.86 170 19.88 2

90 15.15 175 20.16 2

95 15.41 180 20.44 2

100 15.77 185 20.74 2

105 16.08 190 20.99 2

110 16.38 195 21.36 2

two holes is 1.7F0.1 and 1.8F0.1 W m�1 K�1,

respectively (Mongelli et al., 1983).

2.2. New thermal measurements

Two boreholes located in the Tyrrhenian side of the

Apennines chain (GH3 and GH4) were logged

specifically for this study. Temperature measurements

were carried out at 5-m intervals by means of a

precision temperature acquisition system with a 4-

wire shielded cable and equipped with a Pt-resistance

epth (m) Temperature (8C) Depth (m) Temperature (8C)

00 21.63 285 26.75

05 21.96 290 26.95

10 22.27 295 27.19

15 22.60 300 27.47

20 22.92 305 27.70

25 23.25 310 28.02

30 23.55 315 28.35

35 23.84 320 28.76

40 24.16 325 28.97

45 24.46 330 29.18

50 24.76 335 29.39

55 25.07 340 29.60

60 25.35 345 29.80

65 25.66 350 29.98

70 25.96 355 30.16

75 26.26 358 30.34

80 26.51

Fig. 3. Thermal gradient along the boreholes GH3 and GH4. Dots indicate average values for rock thermal conductivity and bars are standard

deviations.


sensor. The total system uncertainty ranges from 0.01

to 0.03 8C.Table 2 shows the data recorded in the borehole

GH3, which crosses flysch-type sediments down to

260 m depth, consisting of shales and marls

alternating limestones, marly limestones and arena-

Table 3

Underground temperatures observed in the borehole GH4

Depth (m) Temperature (8C) Depth (m) Temperature (8C) D

30 18.07 75 23.75 1

35 18.97 80 24.54 1

40 19.73 85 25.20 1

45 20.38 90 25.88 1

50 20.94 95 26.63 1

55 21.47 100 27.47 1

60 22.00 105 28.34 1

65 22.54 110 29.11 1

70 23.06 115 29.97 1

ceous limestones, followed by breccias anhydrites

and phyllites down to the hole bottom (358 m). The

thermogram outlines an average geothermal gradient

of 58 mK m�1 in the uppermost 240 m. At larger

depths it varies from a minimum of 44 and a

maximum of 74 mK m�1 at the lithology change

epth (m) Temperature (8C) Depth (m) Temperature (8C)

20 30.72 165 36.54

25 31.41 170 37.03

30 32.10 175 37.50

35 32.78 180 37.99

40 33.42 185 38.56

45 34.09 190 39.16

50 34.75 195 39.78

55 35.40 200 40.45

60 36.02


which marks the transition between flysch and

breccias, at about 310 m depth. Thermal conduc-

tivity, determined on core samples recovered from

200–300 m depth, has an average value of 2.5F0.7

W m�1K�1, and it tends to be greater when the

geothermal gradient is lower (Fig. 3).

The borehole GH4 reached the depth of 200 m

and encountered shales alternating limestones and

flysch-type levels, more or less hard. Table 3 shows

temperature data, while Fig. 3 depicts the temper-

ature gradient and the thermal conductivity. Only

four cores collected at 100, 130, 160 and 190 m

depth were suitable for laboratory analysis, which

gave a weighted mean thermal conductivity of

2.5F0.15 W m�1 K�1. The average thermal

gradient is very high (130 mK m�1), and the

maximum value (171 mK m�1) is observed at 100

m depth, where the thermal conductivity is lower

(1.7F0.5 W m�1 K�1). The maximum thermal

conductivity (3.7F0.2 W m�1 K�1) corresponds to

Fig. 4. Ground surface temperature (GST) change from inversion of

the calcareous level showing the lowest thermal

gradient of 96 mK m�1.

3. Inversion of data and simulations

The functional space inversion (FSI) technique

was used to calculate the GST histories of the

selected boreholes (Shen and Beck, 1991, 1992).

Data processing was preceded by the evaluation of

different theoretical GST histories to find out the

optimal parameters of the inversion algorithm in

relation to the characteristics of the available bore-

holes, the amplitude and duration of the expected

climatic variations. To this purpose, different simple

models of climatic change have been constructed and

the effect on the underground temperature has been

simulated.

Similarly to other inversion techniques, the FSI

method assumes that heat transfer is only by

temperature–depth data in the boreholes GH1 and GH3–GH8.

Fig. 5. DT observed values (dots) of the borehole GH2. Dashed line

is the theoretical curve calculated from Eq. (1) for a sinusoida

ground temperature model fitting the residual temperature (bold

curve in the inset). For comparison, the GST obtained with FSI (thin

line) is also shown in the inset.


conduction through a one-dimensional medium. The

method requires a priori estimates of the GST

variations (assumed to be zero in our calculations),

the thermophysical parameters and the heat flux,

which all are adjusted simultaneously in the course

of the inversion. Uncertainties in these parameters

are accounted for in a form of a priori standard

deviations (S.D.). This is especially important for

proper treating of the possibly unrecognised steady-

state noise in the measured temperature profile

arising from heterogeneity in the thermal conductiv-

ity, which is a crucial parameter in the GST

reconstruction. Geology at the investigated boreholes

shows for the layered structure negligible 3-D effects

on the subsurface temperature field. Direct thermal

conductivity determinations were available for the

investigated boreholes and a priori S.D. of 0.5 W

m�1 K�1 was assumed. Uniform thermal diffusivity

of 10�6 m2 s�1 and heat production of 1.0 AW m�3

were considered.

In general, inversions of underground temperatures

of the Tyrrhenian side (boreholes GH1, GH3 and

GH4) and of Adriatic side (GH5–GH8) gave con-

sistent results and clearly outline a different climatic

history for the western and eastern edge of the Italian

peninsula (Fig. 4). Results for borehole GH2, shown

in Fig. 5, deviate from the general trend inferred in the

neighbouring boreholes of the Tyrrhenian side, point-

ing to some local effect.

The relative shallow depth of GH2 implies that

the temperature data mainly contain information on

climate variation in the last 100 years. Moreover it

must be stressed that, due to diffusion, FSI can

recover only reasonable long-period features of the

GST history from underground temperature data,

whereas it is unable to resolve short wavelength

events in the distant past (Shen et al., 1992; Harris

and Chapman, 1998). Therefore, in order to gain a

finer detail of the climatic signal stored in this

borehole, a different inversion technique was

applied. We found that the temperature log of GH2

in the 20–80 m depth range matches a surface

temperature harmonic oscillation with a period

P=2p/x and amplitude DTo (Fig. 5). The under-

ground effect of such a variation is given by

DT z; tð Þ ¼ DTocoshexp � gð Þ ð1Þ

l

where h=(xt�g), g=z (x/(2v))1/2, the thermal

diffusivity is v=10�6 m2 s�1 and t is the time

since the variation is maximum. By differentiating

Eq. (1), one obtains the temperature gradient

distribution:

DC z; tð Þ ¼ DTogz

sinh � coshð Þexpð� gÞ ð2Þ

The wavelength k and the propagation velocity v

of the perturbation are given by k=2(pvP)1/2 and

v=2(pv/P)1/2. When z=k, DT(k, t)=0.002 DTo cos 2p[(t/P)�1] (Pasquale et al., 1996). From Eqs. (1) and

(2) it follows that

cosh ¼ 0 for DT z1; tÞ ¼ 0ð ð3Þ

and

cosh ¼ sinh for DC z2; tð Þ ¼ 0 ð4Þ


from which one obtains

xt � z1ðx= 2vð ÞÞ1=2 ¼ p=2 ð5Þ

and

xt � z2ðx= 2vð ÞÞ1=2 ¼ p=4 ð6Þ

where z1 is the first depth at which DT(z, t)=0 and z2is the first depth at which DC(z2, t)=0 (Beck, 1982;

Mongelli and Zito, 1988). Using the thermal diffu-

sivity, z1 and z2, being known from experimental data,

one determines x and t. The value of DTo is

calculated from Eq. (1) by using the DT(z, t) observed

values. By considering a linear pattern of the temper-

ature profile in the range 80–145 m, the background

temperature gradient is 115.6 mK m�1 and the

extrapolated surface temperature is 12.0 8C. The

climatic reconstruction results in a sinusoidal-type

change with amplitude 1.5 K, period 32 years and

time t=21 years.

This type of analysis was also applied to GH1

focussing on the most recent climatic history at this

site. The temperature profile observed in the upper-

most 80 m of the borehole is fitted by a linear change

Fig. 6. As in Fig. 5 for the borehole GH1. The ground temperature

change (in the inset) is of linear type (Eq. (7)).

in the surface temperature of the type DTo=bd t, where

t is the time and b is a constant (Fig. 6), whose

corresponding variation with depth DT(z, t) is given

by (Pasquale et al., 2000)

DT z; tð Þ ¼ bt

�erfc

z

2ffiffiffiffivt

p � zffiffiffiffivt

p ierfcz

2ffiffiffiffivt

p�

ð7Þ

and the integral of the error function is

ierfcz

2ffiffiffiffivt

p ¼ 1ffiffiffip

p exp� z2

4vt� z

2ffiffiffiffivt

p erfcz

2ffiffiffiffivt

p ð8Þ

If the lowermost (80–200 m) quasi-linear section of

the temperature log is considered to be unaffected by

the recent changes in surface air temperature, the least

squares fitting yields a background temperature

gradient of 92.6 mK m�1 and an extrapolated surface

temperature of 12.6 8C. The temperature increase

which fits better the disturbance, i.e. minimizing the

sum of the square differences between the theoretical

and observed borehole temperature data, is that for

DTo=1.6 K and t=12 years.

4. Pre-observational mean temperature

4.1. SAT records

A comparison with the surface air temperature

(SAT) records is useful to evaluate the reliability of

the foregoing interpretations and to which extent

inversion techniques yield meaningful results. There

is a number of historical temperature time series in

Italy. The homogenization of some well-known series,

such as Bologna, Genoa, Rome, etc., previously

stored on paper archives, began in the 1970s and still

continues (Brunetti et al., 2004). Temperature records

have been homogenized taking into account possible

changes in station location and instrumentation,

observational schedules, existing gaps, etc. Records

obtained in such a way were validated with different

statistical tests. Further efforts for widening this

database began in the second half of the 1990s by

including more series and improving the available

database, with the aim of a more precise partitioning

of Italy into different climatic sub-regions. At present

homogenized series of air temperature measurements

are available for central-northern Italy, in particular

Fig. 7. Annual surface air temperature change and its trend of the Tyrrhenian side from the Genoa and Florence meteorological time series in the

period 1814–2000. The curve (polynomial of degree 3) is the best estimate with respect to the average value of the whole recording period.


since 1814 for the Florence Ximeniano Observatory

and for the Bologna University Observatory (Brunetti

et al., 2001, 2004), and since 1833 for the Genoa

University Observatory (Pasquale et al., 1998).

The climate history of the Tyrrhenian side can be

outlined by the surface air temperature change as

inferred from the Genoa and Florence data

expressed as departure from the average value over

the period 1814–2000 (Fig. 7). The trends of the

Genoa and Florence series are similar (Fisher’s

correlation coefficient of 0.87F0.08), thus, the

averaged SAT series in Fig. 7 can be regarded as

representative of the regional temperatures at least

for a 200-km long band on the Tyrrhenian side. The

best fitting polynomial curve shows a minimum

centred at the 1910s and larger temperature values

Fig. 8. As in Fig. 7 for the Adriatic side, from Bologna meteorological time

is the best estimate with respect to the average value of the whole record

at the present-day. Within this general trend, there

are two periods, about 10 year long, in which the

maximum positive departures are 2.5–3.0 K.

Fig. 8 shows the surface air temperature variation

recorded in Bologna (Adriatic side). The polynomial

curve fitting the mean departures over the period

1814–1982 shows a minimum value of 0.5 K centred

in 1860 and a maximum of about 0.25 K in 1945.

The maximum differences from the mean trend are

about 1.7 K in 1822 and �2.4 K in 1856. A

comparison of this series with the dendroclimato-

logical temperature estimates for NW Italy (Marti-

nelli, 2004) also shows significant coincidence,

implying that the SAT record of Bologna may be

representative of a wide region of the Po Basin and

the northern Adriatic Sea.

series in the period 1814–1982. The curve (polynomial of degree 3)

ing period.

Fig. 9. Reduced (dots) and calculated temperatures from combined

meteorological and geothermal data used to infer the POM

temperature for GH1 and GH5–GH8.


These SAT records represent the most reliable

regional information since the beginning of the 1800s.

However, it should be stressed that examined SAT

series show pronounced interdecadal variability,

which can hide the possible warming trends of the

20th century. Another bias can be due to the fact that

the homogenization of the time series was restricted

only to stations on the Italian territory. The main

problem of this procedure is that it does not detect the

inhomogeneities arising from changes in the national

standards of measurements. As discussed by Brunetti

et al. (2004), most of such inhomogeneities could

affect the end of the 19th century, when in many

observatories the standards of equipment position

were changed, and the period of World War II, which

may show gaps in records. According to Bohm et al.

(2001), the influence of these possible hidden

inhomogeneities can cause an underestimation of

temperature trends. Thus, borehole temperature logs,

containing independent non-meteorological data

source, jointly analysed with SAT records, may

provide not only useful information about the long-

term mean temperature for the period prior to the

onset of meteorological observations, but also the

basis for checking this kind of inhomogeneity.

4.2. Assessing POM

Chisholm and Chapman (1992) first tested the

consistency between meteorological and geothermal

data. Since then their joint analysis has been applied

to numerous paleoclimatic reconstructions, thus pro-

viding reliable inferences about temperature variations

over the 20th century (e.g. Pasquale et al., 1998; Bodri

et al., 2001). Pre-observational mean temperature

(POM) is the long-term mean surface temperature

against which 19th and/or 20th century warming can

be referenced. The POM values can be obtained by

comparing the measured borehole temperatures with

the synthetic temperature–depth profiles calculated

under a pure conductive thermal regime, when the

SAT series are used as a forcing function (surface

boundary condition).

The main assumption of this method is that the

ground and air temperatures track. Thus, the POM

value, calculated from the SAT and ground temper-

ature records, reflects the climate change in the

neighbourhood of the borehole. In presence of non-

climatic disturbances, the obtained POM can be

biased. Non-climatic sources for decoupling of the

air–ground temperatures were investigated in numer-

ous works (e.g. Chisholm and Chapman, 1992;

Harris and Chapman, 1998; Beltrami, 2001). In

view of the insignificance of topographic corrections

and groundwater flow in our boreholes, the air–

ground temperature differences might in principle

arise from temporary changes in the near surface

Table 5

As in Table 4, but POM is the long-term mean temperature before

the year 1900

Borehole POM (8C) D (K) ms (K)

GH1 15.58 0.24 0.128

GH5 13.81 0.09 0.041

GH6 13.93 �0.03 0.066

GH7 13.63 0.27 0.036

GH8 14.01 �0.11 0.095


conductive properties. However, as the examined

boreholes were drilled in consolidated rocks, the

subsurface layers cannot be affected by significant

transient variations in moisture content and, corre-

spondingly, in conductive properties. Effect of soil

freezing (e.g. Beltrami, 2001) is similarly insignif-

icant, since it occurs rarely, is short lived and

changes randomly each year.

The change of vegetation and land use in the

neighbouring of the investigated boreholes could

instead produce significant temperature anomalies

(e.g. Majorowicz and Skinner, 1997), which do not

reflect regional air temperature variations. However,

the quantitative description of the nature and the

magnitude of such microclimatic effects is a difficult

problem. There are not many investigations on this

topic (see Bodri et al., 2001, and the references

therein), and in most cases historical changes of the

land use are poorly documented.

In order to calculate POM values the standard

least-square inversion analysis that minimizes the sum

of squared differences between reduced and synthetic

temperature–depth profiles was used (for details of

calculus see Bodri et al., 2001). The POM values were

calculated for GH1 and GH5–GH8. As a forcing

function, we applied the SAT of Genoa and Florence

to the borehole GH1 and Bologna to GH5–GH8. The

POM values were calculated for the period prior to the

beginning of SAT records as well as before 1900.

Boreholes GH3 and GH4 were measured between

1999 and 2000, while the homogeneous SAT records

exist only until 1994. Since the disagreement of the

end of SAT record and the date of borehole logging

can bias the POM estimates (Harris and Chapman,

1997), these boreholes were excluded from consid-

eration. As seen in Fig. 2, the bulk of the observed

Table 4

POM temperatures and rms misfit between the reduced temperatures

and the best fitting SAT–POM synthetic model

Borehole POM (8C) D (K) rms (K)

GH1 15.59 0.23 0.128

GH5 13.76 0.14 0.051

GH6 13.86 0.04 0.074

GH7 13.62 0.28 0.032

GH8 13.90 0.00 0.095

POM temperature is the long-term mean before the beginning of

SAT record. D is the amount of warming as a deviation of the POM

temperature from the 1930–1970 SAT mean.

borehole temperatures represents a quasi-steady-state

geothermal field. The POM values were calculated

from the reduced temperatures, which represent the

departure of the observed temperature–depth data

from the steady-state conditions. Results of reduced

and best-fit calculated temperatures are presented in

Fig. 9.

Results of POM calculations are summarized in

Tables 4 and 5, where we present the obtained values,

relative amounts of temperature change and the values

of the rms misfit. The latter value represents the

measure of deviations of the curve calculated with the

mean squares method from the measurements, and

thus characterizes the goodness of fit. Similarly to the

foregoing GST reconstructions, POM results indicate

difference in the climatic history between the Tyr-

rhenian and the Adriatic sides. In the Tyrrhenian side,

the POM temperature before the beginning of SAT

records and before 1900 is the same, indicating

warming by 0.23–0.24 K. All the boreholes of the

Adriatic side give generally coincident POM values,

which show, on average, slight warming by 0.12 and

0.06 K since 1814 and 1900, respectively.

5. Leftover temperatures

The calculated synthetic temperatures faithfully

match the reduced temperature pattern only for

borehole GH7 (Fig. 9). An rms misfit of ~0.03 K

can be regarded as a result of the noise in the

measurements. Larger values, like for boreholes GH6

and GH8, mean that at least a part of the transient

reduced temperatures cannot be explained by the

regional climatic changes, and may reflect other

disturbing factors. Excepting the foregoing possible

problems due to the hidden inhomogeneities in SAT,

local microclimatic effects could cause the incon-

sistency between the reduced and calculated temper-


atures. These can be due to a variety of factors, such

as variations of agricultural activities or vegetation

cover and urbanization in the surroundings of the

borehole site.

In order to move beyond the regional climatic

contribution and to identify additional local compo-

nents, causing the existing misfits, we investigated the

leftover reduced temperature (Ta), defined as

Ta(z)=Tr(z)�Tc(z), where Tr is the reduced temper-

ature and Tc is the calculated synthetic best fit POM–

SAT temperature (for details, see Cermak et al., 1992;

Cermak and Bodri, 2001). We performed numerous

trial runs with synthetic data, which showed that

inversion of the leftover temperatures can provide

information on the local climatic history.

The significance of the leftover temperatures can

be demonstrated with a simple, synthetically gener-

ated, example of noise-free temperature log for a

homogeneous half-space with thermal diffusivity

v=10�6 m2 s�1. Fig. 10 shows the synthetic reduced

temperature with an accuracy of 0.01 K (truncation

error) at 5 m intervals to the depth of 500 m

corresponding to a surface temperature increase by

0.5 8C during the last 50 years. Let us suppose an SAT

series to be available showing no temperature increase

in the last 100 years, i.e. not containing the recent 50

yearlong warming. In this case, the best-fit curve,

obtained with a constant forcing function, is for a

Fig. 10. (A) Reduced temperatures due to a surface temperature increase b

value of �0.42 K considering an SAT series with no change of surface tem

profile (for details see text).

POM value of �0.42 K. In other words, it would be

inferred warming diffused through the whole obser-

vational period and having somewhat weaker ampli-

tude, than that really occurred. However, despite of

smoothing and diffusion, the POM value gives a

meaningful estimate of the warming occurred during

the observational period.

The differences between the synthetic reduced

temperature and the best-fit curves (leftovers) are

within F0.08 K (Fig. 10 b). Negative temperature

indicates a cooling event, whose characteristics can be

roughly estimated with the formulae developed by

Lachenbruch (1994) and tested by Harris and Chap-

man (1998). The method allows calculating the

parameters of a step change of temperature, also

called bboxcarQ event, from the maximum leftover

temperature Tm, its depth zm and the depth of the

bottom anomalous temperature z2, corresponding to

1% of the surface temperature change. The onset time

of the bboxcarQ event is t2=z22/8v, its duration is D=z2

2/

4v�zm2 /v and the amplitude of the temperature change

is DT=8 Tmzm2 /(z2

2�4zm2 ). In our example zm=69 m,

z2=160 m, and Tm=0.056 K. One obtains that the

onset of cooling occurred 101.6 years ago, its duration

is 52 years and the amplitude �0.33 K. It appears that

the combination of the POM and leftover temper-

atures gives a quite real surface temperature trend. For

the field data, the FSI method can be formally applied

y 0.5 8C in the last 50 years (thick curve) and calculated for a POM

perature in the last 100 years (thin curve). (B) Leftover temperature


on leftover temperature profiles to reconstruct more

complex GST histories.

The leftovers for the boreholes GH1 and GH5–

GH8 are presented in Fig. 11. The most noticeable

leftovers occur in the uppermost interval above 50 m

depth, and range from �0.65 to 0.53 K. The leftover

values decrease rapidly below this depth. In the 50–

200 m interval, leftover temperatures are generally

within F0.1 K and their average value is 0.05 K, thus

comparable with the precision of the temperature

logging. The occurrence of noticeable disturbances

mainly in the uppermost parts of the borehole logs can

be interpreted in terms of recent, local climatic

changes.

The rough estimate of the beginning and amount of

GST local changes can be obtained from inversion of

the Ta profiles by means of FSI. Due to the relatively

high bgeologicQ noise of the available temperature–

depth data and the shallow depth of the boreholes,

results of inversion were considered of significance

only for the last 60–80 years prior to the thermal

logging. All the boreholes indicate a temperature

decrease of 0.8–2.0 K from 1950 to 1960 and since

Fig. 11. Leftover reduced temperatures f

the end of the 1970s. The amount of cooling tends to

increase towards the south. Cooling was preceded by

warming at a rate of 0.3–0.4 K year�1 at boreholes

GH6 and GH8 and a relatively constant warmer

period at borehole GH5, with temperature 0.4–0.6 K

higher than that of the 1970s.

Since the local microclimatic influences have

opposite sign, they can obscure the large-scale

warming trend. There exist different more or less

effective techniques (e.g. averaging over all stations

into single time series) to soften the impact of local

factors and to obtain more general temperature

patterns for a region only from the SAT data. The

advantage of joint processing of SAT and borehole

temperature logs is its ability to distinguish local and

regional climatic changes, which cannot be achieved

when one uses these databases separately.

The local climatic influence is less significant for the

borehole GH1, in the Tyrrhenian side (Fig. 11). The

leftover temperature profile shows local warming of

about 0.4 K in the last 20 years, additional to that

inferred from the SAT records. The amount of warming

for borehole GH1 is almost identical to that of GH7

or boreholes GH1 and GH5–GH8.


(Tables 4 and 5), where the local influence has been

insignificant and more than 90% of observed transient

borehole temperature signal is accounted for by the

SAT history. In both cases POM values obtained for

periods before 1814–1833 and/or 1900 are identical,

which suggests that the whole amount of warming can

be attributed to the 20th century alone.

6. Discussion and conclusions

Our results argue for different patterns in the GST

histories since 1750 between the Tyrrhenian and

Adriatic sides. In the former, the four investigated

boreholes show the same trend. The temperature has

always been lower than that of the 1990s, with

minimum values of �0.5–0.8 K from 1930 to 1960.

It was preceded by a slow decrease of temperature

since 1840 and it has been followed by a warming

phase at a high rate up to now. These results of a rapid

recent warming confirm those inferred for northwest-

ern Italy by Pasquale et al. (1998, 2000).

The warming phase is put into better evidence by

examining in detail the temperature signal in the

uppermost section of the borehole GH1 (Fig. 6). The

climatic model consisting of a linear increase in the

surface temperature during the last 10 years at a rate

of about 0.1 K year�1 accounts for the shallower part

of the underground temperature profile.

The temperature disturbances observed in the

borehole GH2 are well fitted by a short period change

in the ground surface temperature, which shows a

harmonic oscillation during the last three decades.

This trend can hardly be resolved by the FSI method,

which gave quite unstable results for this case. Such

local periodic variations in the surface temperature

could be attributed to cycles of tree cutting followed

by slow re-growth of vegetation.

On the Adriatic side, the magnitude of the inferred

climatic change differs from that of the western side of

the Apennines chain. FSI results indicate that GST has

always been higher than that of the 1980s. After a

warmer period ending in 1940, there has been cooling

until the time of the temperature measurements.

During the latter phase, the temperature has decreased

at an average rate of �0.03 K year�1. Moreover,

inversion shows for boreholes GH5 and GH8 the

beginning of a warming phase between 1970 and

1980. This phase has been also recognised by

Mongelli and Zito (1988).

It appears that all reconstructed GST histories fit

those of the nearby meteorological observatories

records reasonably well, within the well known

limitation that a direct comparison of the borehole

temperature profiles and surface air temperature

records is difficult. Ground temperatures are generally

warmer than air temperatures by 0.5–2.0 K. In

particular, Murtha and Williams (1986) showed that

the vegetation cover as well as the moisture regime

may have a significant effect on the soil temperature,

which could be higher by as much as some degrees

than the mean annual temperature.

By usingminimum andmaximum daily temperature

from 1865 to 1995, Brunetti et al. (2000) obtained a

similar trend of the mean annual surface air temperature

in northern and southern Italy. On the contrary, our

results put into evidence different climatic histories

between the Adriatic and Tyrrhenian sides. The barrier

effect of the N–S trending Apennines ridge and the

destabilising effect of the Mediterranean Sea, which

tend to facilitate the genesis of cyclones west of the

mountain range, are the two main geographical factors

that may explain these different trends.

The results of the POM calculations show that the

warming obtained for the borehole GH1 at the

Tyrrhenian side coincides well with the amount of

warming obtained by Maugeri and Nanni (1998) for

northern Italy. The equality of POM temperatures

obtained for periods before 1833 and 1900 suggests

that all the observed warming occurred in the 20th

century. In the Adriatic side, approximately, half of the

obtained warming occurred already at 19th century.

Even if processing of data from more boreholes

would be recommendable for reaching definitive

conclusions, the available data hint that observed

difference in the course of the climatic history may

have been caused by local climatic changes in the

Adriatic side. The existence of such additional

climatic changes, which cannot be attributed to the

change of climate represented by the SAT observation,

deserves certain explanation. Due to the lack of

detailed information on the land-use processes in

Italy, the reasons for local climate changes can only be

speculated upon. Anyhow, since the long-term mon-

itoring and analysis of indicators of local environ-

mental change, which are sensitive to changes in


climate for most regions of the world, are generally

insufficient and/or absent at all, the investigation of

the leftover temperatures can be regarded as an

additional independent tool to estimate the response

of the local environment to anthropogenically induced

changes, and to reveal the impact of these factors.

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Evidence of climate warming from underground temperatures in NW Italy

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