IL NUOVO CIMENTO VOL. 18 C, N. 1 Gennaio-Febbraio 1995 Thirteen Years of Atmospheric Carbon Dioxide Measurements at Mt. Cimone Station, Italy. V. CUNDARI(1), T. COLOMBO(l) and L. CIATTAGLIA(2) (1) Servizio Meteorologico Italiano - Via delle Ville 100, 41029 Sestola (MO), Italy (2) Istituto di Fisica delrAtmosfera-CNR - Via Tiburtina 770, 00159 Roma, Italy (ricevuto il 25 Ottobre 1993; revisionato il 26 Luglio 1994; approvato il 29 Novembre 1994) Summary. -- The atmospheric carbon dioxide concentration has been continuously measured at Mt. Cimone station from March 1979. In this paper a selection scheme is applied to the measured concentrations in order to obtain data representative of background conditions. Monthly averages, expressed in the WMO X-85 scale are calculated from the selected data and analysed by a technique of time series decomposition until december 1991. Monthly values exibit an increasing long-term trend, mainly due to the fossil fuel combustion: over the whole monitoring period the average C02 growth rate is 1.66 p.p.m.v./y. A seasonal cycle, largely due to the biospheric activity of the northern hemisphere is evident. The estimated average peak-to-peak amplitude is 11.32 p.p.m.v, with a maximum occurring in April and a minimum in August. The seasonal amplitude is found to be decreasing with time, by about 1.5 p.p.m.v, over the entire record: no conclusive interpretations are given about this experimental result. Besides the long-term trend and the seasonal cycle, C02 interannual variations are observed in the selected record; these correlate negatively with the Southern Oscillation Index (SOI) with a maximum correlation coefficient of 0.6 for a delay of about 7-8 months. PACS 92.60 - Meteorology. 1. - Introduction. In the last few decades great effort has been devoted to understanding the increase in the atmospheric carbon dioxide concentration. Although it is generally accepted that the long-term increase in atmospheric C02 concentration is due to fossil fuel consumption, the sources and sinks which contribute to the short-term concentration variations are not well understood or quantified. In particular, much effort has been spent on global measurement programmes which use either continuous monitoring or discrete air samples in flasks. The measurements made at Mt. Cimone (2.165 m a.s.l., 44 ~ 11' N, 10042 ' E, see fig. 1) since March 1979, by the Italian Meteorological Service represent the longest record of continuous COs measurements in Europe that can be considered to be background in nature. There 33
Transcript
IL NUOVO CIMENTO VOL. 18 C, N. 1 Gennaio-Febbraio 1995
Thirteen Years of Atmospheric Carbon Dioxide Measurements at Mt. Cimone Station, Italy.
V. CUNDARI (1), T. COLOMBO(l) and L. CIATTAGLIA(2)
(1) Servizio Meteorologico Italiano - Via delle Ville 100, 41029 Sestola (MO), I taly (2) Isti tuto di Fisica delrAtmosfera-CNR - Via Tiburtina 770, 00159 Roma, I taly
(ricevuto il 25 Ottobre 1993; revisionato il 26 Luglio 1994; approvato il 29 Novembre 1994)
Summary. - - The atmospheric carbon dioxide concentration has been continuously measured at Mt. Cimone station from March 1979. In this paper a selection scheme is applied to the measured concentrations in order to obtain data representative of background conditions. Monthly averages, expressed in the WMO X-85 scale are calculated from the selected data and analysed by a technique of time series decomposition until december 1991. Monthly values exibit an increasing long-term trend, mainly due to the fossil fuel combustion: over the whole monitoring period the average C02 growth rate is 1.66 p.p.m.v./y. A seasonal cycle, largely due to the biospheric activity of the northern hemisphere is evident. The estimated average peak-to-peak amplitude is 11.32 p.p.m.v, with a maximum occurring in April and a minimum in August. The seasonal amplitude is found to be decreasing with time, by about 1.5 p.p.m.v, over the entire record: no conclusive interpretations are given about this experimental result. Besides the long-term trend and the seasonal cycle, C02 interannual variations are observed in the selected record; these correlate negatively with the Southern Oscillation Index (SOI) with a maximum correlation coefficient of 0.6 for a delay of about 7-8 months.
PACS 92.60 - Meteorology.
1. - I n t r o d u c t i o n .
In the last few decades great effort has been devoted to understanding the increase in the atmospheric carbon dioxide concentration. Although it is generally accepted that the long-term increase in atmospheric C02 concentration is due to fossil fuel consumption, the sources and sinks which contribute to the short- term concentration variations are not well understood or quantified. In particular, much effort has been spent on global measurement programmes which use ei ther continuous monitoring or discrete air samples in flasks. The measurements made at Mt. Cimone (2.165 m a.s.l., 44 ~ 11' N, 10042 ' E, see fig. 1) since March 1979, by the Italian Meteorological Service represent the longest record of continuous COs measurements in Europe that can be considered to be background in nature. There
33
34 V. CUNDARI, T. COLOMBO and L. CIATTAGLIA
10~ ' E
Fig. 1. - Mt. Cimone location and its surrounding geographic area.
44 ~ 11' N
are other European background monitoring programmes reported in [1], but these either have quite short records (Zugspitze by Germany) or operate stations outside of continental Europe (Amsterdam Island by France, Izafia in the Canary Islands by Spain). Other stations operated by Germany (Schauinsland and Westerland) and Hungary (K-Puszta) do not strictly satisfy the requirements for background monitoring.
The first seven years of measurements at Mt. Cimone have been reported previously [2]. As with many other CO2 programmes, measurements were based on C02-in-N~ reference standards for which the ,,carrier gas correctiom~ [3] had to be determined. In September 1987, the standards at Mt. Cimone were changed to CO2-in-air and the appropriate correction for the non-dispersive infrared (NDIR) analyser was determined by Cundari et al. [4]. This correction has been applied to all of the data prior to September 1987. The updated measurements presented here have been converted to the World Meteorological Organization (WMO) COs Central Laboratory (CCL)X-85 C02-in-air calibration scale. This paper is divided into three parts: a discussion of the sampling protocol and measurement system including a critical review of the calibration scale stability throughout the measuring programme; the operational definition of background data and the procedure for selecting background data from the continuous record; and, finally, an analysis of the long-term trend, the seasonal cycle and the interannual changes in the selected record.
THIRTEEN YEARS OF ATMOSPHERIC CARBON DIOXIDE MEASUREMENTS ETC. 35
2 . - I n s t r u m e n t a l .
Continuous observations of atmospheric CO2 concentration at Mt. Cimone began in March 1979 using an URAS-2T NDIR analyser[5]. The analyser was calibrated automatically every two hours by switching 2 span gases into the air stream to check the instrument response. The data acquisition system integrated the analyser output signal over hourly or half hourly periods and, in addition, the signal was recorded on a strip-chart recorder for visual inspection. The internal precision of these routine measurements, that is the reproducibility of measurements obtained several days apart, was estimated to be within _+ 0.3 p.p.m.v. In November 1988 and ULTRAMAT- 5E NDIR analyser together with a digital system, was installed for routine measurements [4]. As a result of these changes the internal precision increased to about _+0.1 p.p.m.v. With the current data acquisition system, the output of the analyser is digitized and processed by computer to calculate one-minute means, from which the ten-minute and hourly means with the relative standard deviations are computed.
As a further check on the integrity of the new system, a second similar but independent system was set up temporarily in February-March and May-June 1992. During the first test period (February-March) the Mt. Cimone ULTRAMAT- 5E NDIR analyser was compared with an identical one provided by the CRTN- ENEL electricity supply agency (Milano) for a period of twenty days. This analyser was replaced by an URAS-3G NDIR analyser during the May-June period for a further twenty days of testing. The differences in C02 daily means between the original and the additional systems were calculated. Although the differences (fig. 2) sometime exceeded _+ 0.15 p.p.m.v, by a few hundredths of a p.p.m.v., the global result suggests that the instrumental uncertainty of routine measurements, using the ULTRAMAT-5E analyser or the URAS-3G analyser, is excellent.
2"1. C a l i b r a t i o n s ca l e . - From the beginning of the program in March 1979 and until September 1987 six C02-in-N2 mixtures, ranging from 310 to 340 p.p.m.v., were used as our reference standards in calibrating the analyser. The six mixtures, provided in 40-1itre high-pressure stainless-steel tanks by the WMO-CCL of the Scripps Institution of Oceanography (SIO), La Jolla, California were subdivided into primary and secondary reference standards. The three secondary standards were flushed in the analyser about every ten days to calibrate the working gases. All six standards were flushed at least four times per year in order to assess the consistency of the calibration scale with time. No measurable drifts of the concentrations of the three secondary vs . the three primary standards were detected.
By September 1987 four CO2-in-synthetic-air 50-1itre stainless-steel tanks were introduced as our new reference standards. Concentrations, ranging from 320 to 360 p.p.m.v, in the WMO X-85 scale, were determined at the WMO-CCL.
The carrier gas error has been calculated with an estimated absolute limit uncertainty below 0.4 p.p.m.v. [4]. In the correction procedure of the previous meas- urements we assumed that the carrier gas error was constant in time.
At the beginning of 1988 we noted a progressive drift of our scale due to stability problems of the standards. While a set of new standards would be provided by the WMO-CCL, an intercomparison programme was started with the support of the Gas Standard Laboratory of the Atmospheric Environment Service (AES), Toronto, Canada.
36 v. CUNDARI, T. COLOMBO and L. CIATTAGLIA
0.20
0.00
~" -0.20 , 25 2 ' 7 ' 2 ' 9
r/]
~ February 0.20
March 1992
0.00
-0.20 2 7 ' 2 ' 9 ' ' ' ' ' i ' 0 ' 1'2 ' 1'4
May June 1992 time (day)
Fig. 2. - Differences in C02 daily concentrations between two independent measuring systems at Mt. Cimone. The two systems were set up in February-March (top) and May-June (bottom) 1992. For the f'rrst test period two ULTRAMAT-5E (Siemens) NDIR analysers were operated, after an ULTRAMAT-5E and URAS-3G (H&B) NDIR analysers were used.
Five CO2-in-natural-dry-air mixtures in the range 320--380p.p.m., in 40-1itre aluminium tanks, were shipped to Mt. Cimone by the AES, and used in April 1991 to correct our scale.
Seven intercomparisons were performed on different days. The result was our ,(first-step- corrected scale tied to the WMO X-85 scale. In order to improve the accuracy of our measuring scale, a set of eight COe-in-dry-natural-air, 10-1itre mixtures in aluminium tanks, was used. Concentrations were determined at Mt. Cimone in May 1991 and then at the AES Laboratory in the period October 1991- February 1992. Results of the measurements are listed in detail in table I. The Mt. Cimone scale was higher over the entire measuring range by 0.19 p.p.m, at least.
A ,,second-step- correction of Mt. Cimone scale was calculated on the basis of the two exercises, made both with the five AES gases and our eight mixtures.
When the AES Laboratory returned our eight tanks, a new determination of their concentrations was carried out in March-April 1992. Details of the results are given in table II and show that the agreement is within approximately 0.1 p.p.m.v, over the entire C02 measuring range.
The final correction of our scale was calculated on the basis of the three deter-
THIRTEEN YEARS OF ATMOSPHERIC CARBON DIOXIDE MEASUREMENTS ETC. 37
TABLE I. - Intercomparison between AES and Mt. Cimone (May 1991; October 1991 - February 1992). C02-in-dry-natural-air concentrations (p.p.m.v.) are expressed in the WMO X-85 scale revised in July 1991. The Mt. Cimone concentrations are the averages of four distinct meas- urements made on different days in May 1991. Tanks are lO-litre aluminium cylinders.
TABLE II. - Intercomparison between AES and Mt. Cimone (October 1991 - February 1992; March-April 1992). C02-in-dry-natural-air concentrations (p.p.m.v.) are expressed in the WMO X-85 scale revised in July 1991. The Mt. Cimone concentrations are the averages of four distinct measurements made on different days in March-April 1992.
minations made at Mt. Cimone in April 1991, by the five AES gases, and, in May 1991 and March-April 1992, by our eight mixtures.
3. - B a c k g r o u n d d a t a s e l e c t i o n .
C02 background concentrations are measuremen t s representa t ive of the global a tmosphere unaffected by local conditions, useful to document the C02 long- term changes in the a tmosphere and spatial gradients at large scale. Here a statistical approach is presented in order to select a set of background data reject ing measuremen t s affected by local influences. Exper ience shows tha t background C02 measu remen t s made at remote sites present a very small variability at shor t t ime scale, i.e. within an hour and f rom an hour to the next [6] because of the good mixing of a tmospheric compounds; this basic assumption has been used as an operational cri terium for our pourpose, i.e. we have considered C02 concentration low variabili ty
38 v. CUNDARI, T. COLOMBO and L. CIATTAGLIA
to identify a set of background measurements from our original data set. Mt. Cimone is not really very far from sinks and sources of CO2 like other stations, however it has some baseline distinctive features. For this reason our analysis attempts to combine two opposite goals, on the one hand the need to maintain as many data as possible, on the other to dentify when background conditions occur. The selection scheme is applied to the hourly COe averages and substantially follows the procedure proposed by Thoning et. al [7] for processing the Mauna-Loa C02 hourly data, although, in our case, a larger variability of the concentrations is allowed.
A preliminary selection regards the vegetative period of the year, ranging at Mt. Cimone from the middle of May to the middle of September. In this period the photosynthetic activity of the local vegetation, growing in the valleys more than 500 meters below, affects the C02 measurements producing a systematic depletion of several p.p.m.v.'s in the diurnal COe concentrations[8]. We decided to reject all hourly averages from 09.00 a.m. LT to 09.00 p.m. LT for the mentioned period of the year.
After the removal of the C02 hourly averages clearly affected by the local photosynthetic uptake, the selection procedure was developed in three subsequent steps:
- - First, all hourly averages with a standard deviation higher than a cut-off value were rejected. In such a manner, depending on the choice of the ~ value, we retain
concentrations that have low within-hour variability. Hourly standard deviations were calculated as shown later in this section.
Second, consecutive hours that differ in concentration by more than a fixed value k were removed. Depending on the choice of the k value, we remove from the record concentrations with high hour-to-hour variability.
- - Third, by means of an iterative method using a run-test smoothing cubic spline [9,10] we were able to reject some outlier hourly averages that could have been remained after the previous two steps. The method implies the thoice of a cut-off value r. The hourly averages were interpolated on one-month time basis by a spline curve and the values that presented a residual from the curve more than r were rejected. The process was reiterated three to five times until no hourly average were removed.
Finally, all the hourly averages rejected by the iterative method were readmitted if their residuals from the last curve were less than or equal to r.
As an example, the raw hourly averages and the selected hourly averages at Mt. Cimone for 1989 are plotted in fig. 3, after having imposed 8= 0.25p.p.m.v., k = 0.30p.p.m.v. and r--0.50p.p.m.v. The choice of the three parameters is subjective and should represent a compromise, so that only the background measure- ments are retained and, at the same time, a very large number of hourly values is not removed. From 1989 to 1991 we selected eight different sets of hourly averages by using the eight combinations of the following values: ~ = 0.25 and 0.35 p.p.m.v.; k = 0.20 and 0.30 p.p.m.v.; r = 0.40 and 0.50 p.p.m.v., where hourly standard devia- tions were calculated from the one-minute C02 averages. As stressed in the previous section, hourly standard deviations are not available before 1989, because at that time we did not file the one-minute averages. Information about the instability of the hourly concentrations can be inferred exclusively by the analogue trace taken on a strip-chart recorder. By applying a graphical method to the recorder trace, we
THIRTEEN YEARS OF ATMOSPHERIC CARBON DIOXIDE MEASUREMENTS ETC. 39
o ~
O o
c f
380
370
360
350
340
330
365 I
3 5 5 f
345
335
�9 :'" " : " - " .... '
- ,
!~.i' i' i ; ~i ~, ': : : ':.,: ~, 1989
' ' J , t ,
J F M A M J J A S O N D
~ " ~ ~, � 9 i , '~ . l~ t ,- �9
)
t f F i i
J F M A M J J A S time (month)
L I I
O N D
Fig. 3 . - An example of raw hourly C02 concentrat ions (top) and background selected concentrations (bottom) at Mt. Cimone, 1989 (for the selection scheme see text)�9
selected the hourly averages with standard deviations less than 0.30p.p.m.v. The procedure is not rigorous, because of the subjective interpretation of the recorder trace by the operator. A comparison for 1991, in which hourly standard deviations are available, shows that hourly averages are removed or accepted by the graphical method with an uncertainity of the cut-off value within -+ 0.10 p.p.m.v. Because of this problem, until 1988 the distinct sets of selected hourly averages were fLxed to be four instead of eight, obtained by the following values: e = 0.30_ 0.10p.p.m.v.; k = 0.20 and 0.30 p.p.m.v.; r = 0.40 and 0.50 p.p.m.v. Daily averages were calculated from the selected hourly average sets and from the daily averages the C02 monthly averages were determined. We had four monthly averages per month until 1988 and eight mounthly averages per month starting from 1989.
To each month we attributed an unequivocal average value given by the arithmetic mean of the four or the height values. In table III the calculated unequivocal monthly averages (UMA) are listed, together with the monthly averages calculated from the raw data set. Standard deviations, s, of the four or eight monthly
40 v. CUNDARI, T. COLOMBO and L. CIATTAGLIA
TABLE III . - Monthly and annual averages of C02 concentration in p,p.m.v, at Mt. Cimone. Columns labeled R a w a n d S.d. contain the monthly averages and standard deviations calculated from the raw daily values. Columns labeled UMA and s contain the monthly averages and standard deviations obtained from the background selected daily concentrations. f is the percentage of the hourly averages retained after the selection procedure.
values with respect to the relative UMA are reported too. Note that the s-values are statistical uncertainties of the UMA due to the selection procedure. In the last column, for each month, the mean relative frequency, fi of the hourly values retained after the selection scheme is shown. A very large number of measurements has been sacrified, particularly in summer-time when a strong local influence of the vegetation is present. However, the amount of accepted data is significantly higher than data normally produced by intermittent flask programmes.
4. - Data analysis.
An analysis of the C02 record at Mt. Cimone is carried out with the background selected monthly averages (UMA) listed in table III and plotted as a function of time in fig. 4. The prominent features of the data series are an upward long-term trend and a seasonal cycle. The long-term trend can be regarded as an almost steadily increasing signal substantially due to the fossil fuel combustion. The seasonal oscillation, linked to the biospheric activity of the northern hemisphere, presents recurrent maximum values of the C02 concentration at the beginning of the spring and a depletion in summer with a minimum normally occurring in August. In order to represent the entire behaviour of the monthly series, we assume the time series
Fig. 4. - Monthly C02 concentrations (UMA values listed in table III) at Mt. Cimone obtained by background selected data. The smoothed curve, determined by the STL decomposition procedure, represents the long-term trend.
additive model
(1) C(n) = T(n) + S(n) + R ( n ) ,
where n is the time in months, T(n) denotes the long-term trend, S(n) is the seasonal component and R(n) describes the remaining patterns. The R(n) component picks up C02 fluctuations ranging from month to month up to the interannual changes.
4"1. Long-term trend. - Three distinct algorithms were utilized to find the trend component T(n). Algorithms are only briefly discussed here, for an exhaustive presentation of the subject we refer to the literature. In the first approach we calculated a 12-month-centred running mean of the C(n) values for n = 1, ..., 154; twelve monthly values were lost in the process. The running mean values were then fitted by a smoothing cubic spline function T(t), defined at any value of time along the record. The function T(t), with a continuous second derivative, was designated to represent the T(n) component for t = n. In order to find an appropriate smoothed curve T(t), a parameter p must be specified in the range [0, 1] [11,12]; decreasing p makes the curve smoother. Rapid C02 fluctuations into the curve are undesired because most likely these are not due to the fossil fuel combustion. We decided to chose p = 5.8-10 -5, which gives a 50% attenuation of the running mean signal on a period of 6 years.
The second approach we adopted was a procedure for decomposing a time series into trend, seasonal and remaining components, using the STL computer program by Cleveland [13]. In the use of STL two parameters have to be specified: a trend and a seasonal window size, both expressed as a fraction of the total time series length. We chose the trend parameter equal to 0.45 and the seasonal parameter equal to 1. The third procedure is based on complex demodulation [14,15]. By this technique the Mt. Cimone C02 monthly series is again decomposed into trend, seasonal and remaining
THIRTEEN YEARS OF ATMOSPHERIC CARBON DIOXIDE MEASUREMENTS ETC. 4 3
components. The algorithm starts computing the seasonal component by the expression
St = Rlt cos (2r:/12 + mlt) + R2t cos (27:t/6 + m2t),
where Rlt, mlt and R2t, m2t are slowly changing amplitudes and phases of the 12-month and 6-month cycles. The estimated seasonal component was subtracted from the monthly averages. The residual values were then smoothed by a cubic smoothing spline to describe the trend component. The stiffness of the curve was regulated by choosing the parameter p = 5.8.10 .5 . One year at the beginning and at the end of the record was lost in the process.
In fig. 4 the long-term trend as found by STL is depicted. It is essentially identical for the three methods with the exception that the STL curve is extended over the whole length of the record. The resulting average C02 increase is 1.66p.p.m./y.
4"2. Seasonal cycle. - The seasonal component at Mt. Cimone has been calculated by using the STL procedure. The window size values for STL were the same as specified in the previous section. By an appropriate choice of the window values, STL constrains the seasonal signal to vary slowly from year to year so that the C02 interannual variations are purposely included in the remaining component R(n). At the top of fig. 5 the obtained seasonal cycle S(n) is shown. The maximum of concen- tration occurs in April and the minimum in August; the mean peak-to-peak amplitude is 11.32 p.p.m.v, with a standard deviation of individual years of 0.58 p.p.m.v.
The long-term change of the amplitude of the seasonal component has been investigated by a number of researchers. The attention was principally centred on the Mauna Loa (19~ 155~ record for which a statistically significant increase of the seasonal component was found from the beginning of the monitoring programme, in 1958, to the early years '80 [16, 17, 7]. The record of Ocean Weather Station P (50 ~ N, 145 ~ W) was analysed by Keeling et al. [18] from 1969 to 1981 and by Chang et Wong[12] from 1971 to 1979. Both these studies present a significant increase of the seasonal signal as well. These results have been explained, at least in part, by an increasing of plant activity induced by the global rise of the atmospheric C02 concentration. Chang did not fmd any significant change for Point Barrow (71019 ' N, 156~ and Alert (82027 ' N, 62~ stations for the period 1975 to 1981 and 1977 to 1985, respectively. Examination of the South Pole C02 record by Thompson et al. [15], from 1973 to 1982, leads to the conclusion that the increase, present before 1978, has not continued until 1982; as stressed by the authors the same doubt exists with respect to this result because of the use of a combined data set. The seasonal amplitude at Mt. Cimone is plotted in fig. 6, computed as the difference between the C02 maximum and minimum of the S(n) series for each year from 1979 to 1991. The behaviour indicates that the C02 seasonal amplitude has decreased over the entire record by approximately 1.5 p.p.m.v. This result, even if related to a different period, is opposite to the Mauna Loa and Ocean Weather Station P results. Hypothetical causes of a decrease of the seasonal amplitude, for high northern latitudes, are presented in the paper of Chang et Wong[12]. Arguments pre- sented there, taking into account the winter-season photosynthetic activity of the boreal forests, could support the Mt. Cimone behaviour. Anyway, because of the shortness of the record we have to use some caution in drawing conclusions about our experimental results. Conclusive comments should be deferred to
Fig. 5. - Detrended seasonal cycle (top) and remaining component (bottom) at Mt. Cimone using the STL decomposition procedure. Data are plotted at monthly intervals.
the near future, also in light of the findings of other long-term operating prog- rammes.
In order to roughly estimate the statistical uncertainty of the seasonal amplitude illustrated in fig. 6, a Monte Carlo method was used. The R(n) series, calculated from eq. (1) and graphed in the bottom panel of fig. 5, turns out to be poorly autocorrelated; the correlation coefficients for all lags do not exceed 0.2. The distribution of R(n) values can be regarded as normal with mean m = 0 and standard deviation s = 0.89 p.p.m.v, at a significance level of 70%. We generated 100 artificial R(n) series with a Gaussian distribution having a mean m and a standard devia- tion s. The R(n) series were added in turn to the T(n)+ S(n) term in order to obtain 100 synthetic monthly C02 series C(n). The STL decomposition was applied to the synthetic monthly C02 series and 100 synthetic S(n) series were extracted. The amplitudes were calculated for the 100 S(n) series as in fig. 6, and at each month the standard deviation was computed from the 100 synthetic amplitudes. Standard deviations are plotted in fig. 6 at each time point indicating the standard error estimate.
THIRTEEN YEARS OF ATMOSPHERIC CARBON DIOXIDE MEASUREMENTS ETC. 45
Fig. 6 . - Amplitude behaviour of the detrended seasonal cycle and its error estimate at Mt. Cimone.
4"3. Growth rate. - The residual series R(n) has been fit to a smoothing cubic spline curve R(t) to represent the interannual fluctuations. The fit was done ignoring the higher-frequency variations, so the smoothing parameter p was taken to be 1.9.10 .8 wich give s a half-attenuation period of 30 months. From the sum T(t) + R(t) the first time derivative was calculated in order to obtain the instantaneous growth rate of the long-term trend plus the interannual fluctuations at Mt. Cimone. Figure 7 shows the d(T(t) + R(t)) /dt curve; in the figure, for comparison, the growth rate as an average of three representative baseline stations in the world is also plotted: South Pole (Amundsen Scott Base), Mauna Loa and Point Barrow (for the period 1979-1990). Background selected monthly averages of the three stations were derived from the report Trend '91 [1]. Similar features are evident in the two curves, in particular: a growth rate maximum in 1983 followed by a minimum in 1984 and a maximum at the beginning of 1988 followed by a minimum at the end of 1989. This qualitative agreement suggests that world-wide phenomena should be considered responsible, at least in part for the interannual COe changes. Several studies stressed the existence of a negative correlation between changes in the C02 growth rate and the Southern Oscillation Index (SOI) [19,18, 10,20] which is defined as the difference in the monthly sea level barometric pressure between Tahiti (in the mid-Pacific, 159~ and Darwin (Australia 130~ Low SOI corresponds to a large-scale atmospheric and hydrospheric phenomenon called E1-Nifio[21]. It appears roughly ever 3-4 years for 12 to 18 months. High SOI is associated with a regime of stronger- than-average trade winds (La-Nifia event). For the period of the Mt. Cimone CO2 measurements, two E1-Nifio events occurred, the first, classified as very strong in 1982-83, the second in 1986-88, and one La-Nifia event in 1988-89 (see fig. 7). Here a cross correlation has been calculated between the 5-month running mean SOI values[22,23] considered as input series and the term d(T(t )+ R(t)) /dt at sampling intervals of one month for the period 1979-89. The maximum of the correlation was found to be - 0.60 with time lags of about 7 months. This result is consistent with the
Fig. 7. - Top panel: A comparison of the CO2 growth rate determined as an average of three SIO sites at South Pole, Mauna Loa (Hawaii), Point Barrow (Alaska) (dashed curve) and Mt. Cimone (solid curve). Bottom panel: Southern Oscillation Index.
previously mentioned studies. The mechanisms connecting the COs growth rate to the SOI is not yet well understood, however a more detailed discussion of this topic is beyond the aim of this paper.
5. - C o n c l u s i o n s .
Our recent efforts to improve the instrumental performance have led to a satisfactory precision of the routine C02 measurements, normally within about _+ 0.1p.p.m.v. Within the available f'mancial support, efforts have been made to maintain an internal consistency of our C02 measuring scale. In particular the calibration exercises carried out in cooperation with the AES-Gas Standard Laboratory during 1991-92 allow us to express C02 data in the universally adopted WMO X-85 calibration scale. In this paper a -steady-condition- approach has been adopted in order to select background measurements. Unfortunately a large number of data is rejected because the measuring site is not strictly remote but partially affected by local influences. Furthermore, short-time C02 variations can occur with regional- or wider-scale air-mass changes [2].
The analysis of the background C02 measurements shows an increasing long-term trend, the average rate of the annual increase is 1.66p.p.m.v. The seasonal amplitude shows a decreasing trend; this result is not corroborated by the findings
THIRTEEN YEARS OF ATMOSPHERIC CARBON DIOXIDE MEASUREMENTS ETC. 47
from other stations also if data analysed are related to different time periods. We need more years of measurements to make this question clearer. The COB growth ra te has been found to correlate to the SOI with a delay of about 7 months.
We are grateful to N. Trivet t and E. Darrel of Atmospheric Environment Service, Toronto, Canada, for their cooperation in calibrating the Mt. Cimone C02 measuring scale. We thank P. Bacci of E N E L - C R T N Agency, Milano, who supported our instrumental tests; we thank A. Capasso for assistance in conducting C02 measurements and data processing.
R E F E R E N C E S
[1] BODEN T. A~, KAISER D. P., SEPANSKI R. J. and STOSS F. W. (Editors), Trends '91: A Compendium of Data on Global Change, ORNL/CDIAC-65 (Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, Oak Ridge, Tenn., USA).
[2] CIATTAGLIA L., CUNDARI V. and COLOMBO T., Vellu8 B, 39 (1987) 13. [3] PEARMAN G. I., BEARDSMORE D. J. and O'BRIEN R. C., The CSIRO (Australia) atmos-
pheric carbon dioxide monitoring program: ten years of aircraft data (CSIRO Division of Atmospheric Physics) Tech. Paper 45 (1983), p. 113.
[4] CUNDARI V., COLOMBO T., PAPINI G., BENEDICTI G. and CIATTAGLIA L., Nuovo Cimento C, 13 (1990) 871.
[5] CIATTAGLIA L., J. Geophys. Res., 88 (1983) 1331. [6] GILLETTE D. A., KOMHYR W. D., WATERMAN L. S., STEELE L. P. and GAMMON R. H.,
J. Geophys. Res., 92 (1987) 4231. [7] THONING K. W., TANS P. P. and KOMHYR W. D., J. Geophys. Res., 94 (1989) 8549. [8] CUNDARI V. and COLOMBO W., Ann. Geophys. B, 4 (1986) 13. [9] DE BOOR C., Appl. Math. Sci~, 27 (1978) 392.
[10] CONWAY T. J., TANS P., WATERMAN L. S., THONING K. W., MASARIE K. A. and GAMMON R. H., TeUus B, 40 (1988) 81.
[11] ENTING I. G., J. Geophys. Res., 92 (1987) 10977. [12] CHANG Y. H. and WONG C. S., Tellus B, 42 (1990) 330. [13] ELLIOTT U. P. (Editor), The statistical treatment of CO 2 data records, NOAA Technical
Memorandum ERL-AEL-173 (Silver Spring, Md.) 1989, p. 131. [14] BLOOMFIELD P., Fourier Analysis of Time Series: An Introduction (John Wiley, New York,
N.Y.) 1976, p. 258. [15] THOMPSON M. L., ENTING I. G., PEARMAN G. I. and HYSON P., J. Atmos. Chem,, 4 (1986) 125. [16] CLEVELAND W. S., FREENY A. E. and GRAEDEL T. E., J. Geophys. Res., 88 (1983) 10934. [17] BACASTOW n. B., KEELING C. D. and WHORF T. P., J. Geophys. Res., 90 (1985) 10529. [18] KEELING C. D., WHORF T. P., WONG C. S. and BELLAGAY R. D., J. Geophys. Res., 90 (1985)
10511. [19] BACASTOW R. B., ADAMS J. A., KEELING C. D., Moss D. Z., WHORF T. P. and WONG C. S.,
Science, 210 (1980) 66. [20] GAUDRY A., MONFRAY P., POLIAN G., BONSANG G., ARDOUIN n*, JEGOU A. and LAMBERT
G., TeUus B, 43 (1991) 136. [21] WMO, E1 Ni~o phenomenon and fluctuations of climate, No. 649 (Geneva, Switzerland)
1986, p. 46. [22] Japan Meteorological Agency, Monthly Report on Climate System 1983-1989. Long-range
Forecast Division (Forecast Department, JMA, Tokyo, Japan). [23] Climate Analysis Center, Climate diagnostics bulletin: March 1986, NOAA/NWS
(National Meteorological Center, Washington, DC, USA) 1986.
