Annual and seasonal surface air temperature trends in Mexico

INTERNATIONAL JOURNAL OF CLIMATOLOGY Int. J. Climatol. 29: 1324–1329 (2009) Published online 3 December 2008 in Wiley InterScience (www.interscience.wiley.com) DOI: 10.1002/joc.1787

Annual and seasonal surface air temperature trends in Mexico Edgar G. Pavia,* Federico Graef and Jorge Reyes CICESE, Ensenada, BC, 22860, Mexico

ABSTRACT: Maximum and minimum surface air temperatures (Tmax , Tmin ) throughout Mexico were analysed to look for a regional sign of climate change. Temperature (T ) records were divided into two periods: early (1940–1969) and recent (1970–2004); and the analysis was performed for the four seasons plus the annual average. For these 20 cases, and for each of ∼1400 selected stations, time series were constructed and their linear trends (m) were obtained. The statistical significance of m was tested by posing the null hypothesis m = 0, i.e. that there was no trend. The length of the time series (n) considered for this test was the n-effective (neff ) that takes into account the fact that consecutive values of T have non-zero correlation. The null hypothesis was rejected in less than 25% of the stations in all cases. The principal findings are: (1) Mexico warmed up during the recent period, and this warming was more generalized in Tmax than in Tmin and in summer than in the other seasons; (2) Mexico cooled down during the early period, and this cooling was more generalized in winter than in the other seasons; (3) In neither of these two cases El Niño-Southern Oscillation (ENSO) seems to play any direct role; (4) In contrast to ENSO, the trends and phases of the Pacific Decadal Oscillation (PDO) are consequent in both cases: a warming trend at the beginning of the 1970s and a warm PDO phase prevailing during the recent warming period; as well as a cooling trend at the beginning of the 1940s and a cold PDO phase prevailing during the early cooling period; and (5) north-western and central Mexico temperature trends often contrast with those of the rest of the country. Copyright  2008 Royal Meteorological Society KEY WORDS

Mexico climate; surface air temperature; trends

Received 9 June 2008; Revised 25 September 2008; Accepted 28 September 2008

1.

Introduction

It is now generally agreed that there has been a significant increase in surface air temperature (T ) in most regions of the globe during the past recent decades (IPCC, 2007); nevertheless this increase has marked temporal and spatial differences. For instance, mean air temperature trends in the Southern Hemisphere (Jones, 1994), and particularly in Australia (IPCC, 2007), seem to have been consistently positive since the 1950s; whereas the same trends over North America (IPCC, 2007), and particularly over Mexico (Englehart and Douglas, 2004), appear to have changed sign from negative in the 1940s to the 1970s period to positive in the 1970s to the 2000s period. In this last case even other related variables appear to show a similar behaviour; for example, Englehart and Douglas (2005) report that regional-scale trends in the diurnal range of T over Mexico present negative trends for the 1940–1970 period and positive trends for the 1971–2001 period. Therefore, for the case of Mexico, the statement that the country has warmed up in recent decades (or at least since 1971) seems to be well-justified; nevertheless questions remain regarding the nature of this warming, for example: Are there places within * Correspondence to: Edgar G. Pavia, CICESE, San Diego, CA 921434844, USA. E-mail: [email protected] Copyright  2008 Royal Meteorological Society

Mexico with negative (instead of positive) temperature trends during this period? Are these temperature trends statistically significant? Or what is the role, if any, of the El Niño-Southern Oscillation (ENSO) phenomenon or of the Pacific Decadal Oscillation (PDO) on temperature trends over Mexico? Consequently, in this paper we revise all reliable T data from each available Mexican station, mainly because global warming could mean drier conditions for Mexico (Liverman and O’Brien, 1991); but also because we think that concealed within positive(negative-) trend regional averages [see, for example, Englehart and Douglas (2005)], there are key regions where stations may exhibit trends which are either zero or statistically significant different than zero but negative (positive). Since it appears that a general consensus on a recent global warming has been achieved, we believe it is important to describe the details of this warming, and the purpose of this work is to take a step towards this goal for the particular case of Mexico.

2.

Data

In the last hundred years there have been more than 6000 climatological stations throughout Mexico; although the coverage in time and space of these stations has been

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Table I. Average number of available selected stations (N5 ) during a 5-year period. 5-year period

N5

1940–1944 1945–1949 1950–1954 1955–1959 1960–1964 1965–1969 1970–1974 1975–1979 1980–1984 1985–1989 1990–1994 1995–1999 2000–2004

172 312 459 671 1010 1236 1307 1310 1266 1,136 1055 1020 701

rather inhomogeneous. Available T data from about 5000 stations date back to the early 1940s; but since the 1970s there has been a decrease in the number of climatological stations. This is somewhat reflected in the number of stations selected in this work (Table I); the selection criteria applied to these stations are described ahead. The stations that were eliminated from the original set tend to be located in non-urban areas. It is possible that this fact may affect our results, as the relative number of urban stations increases and this may reflect heat-island effects. However, in the most recent period, the majority of the selected stations (∼60 to ∼80%, depending on the case) were located in non-urban settings (Table II). Thus, from a newly released data-set [the Eric III data base, available from the Mexican water authority (Comisión Nacional del Agua)], we first extract the daily maximum and minimum surface air temperatures subsets which are used in this paper. Second, we estimate their monthly means for all months missing less than 10 days of data. Third, we calculate seasonal means (winter: January–March, spring: April–June, summer: July–September, fall: October–December) when at least two of their monthly means are available. Fourth, we calculate annual means for stations having all their corresponding seasonal means. Fifth, we select all stations having more than 30 years of

annual means; resulting in 1391 stations with (not necessarily simultaneous or continuous) seasonal and annual mean temperatures (of both: Tmax and Tmin ) from 1923 to 2004. Sixth, from these stations we select two periods: early (1940–1969) with 1296 stations, and recent (1970–2004) with 1376 stations; in both cases to be included in a particular period a station must have at least 4 years of data in it. These two periods are chosen because they are similar to those in Englehart and Douglas (2005), that is: 1940–1970 and 1971–2001, also 1970 corresponds to the inflection point of a second degree polynomial fitted to the average time series of all stations considered; and furthermore, it could be argued that global temperature anomalies began a positive tendency from the late 1960s to the early 1970s (Brohan et al., 2006). The above results in 26 720 T time series (two variables: Tmax and Tmin , times five cases: four seasons plus annual, times the sum of the number of selected stations from each period). 3.

Statistical analysis

We begin by least-squares fitting each of the 26 720 T time series to a straight line, i.e.: Test = T0 + mt

(1)

where Test is the model T , T0 is the trivial ordinate at the origin, m (the line’s slope) is the estimated trend, and t is time in years. Theoretically the variance of m is (Wigley, 2006) σ2 (2) α= n 2 (ti − t) i 2

where σ is the population value for the variance of the residuals (in general not known), ti is the ith year where we have data, n is the number of years in the series and t is the mean value of time. Since an unbiased sample estimate of σ 2 is the mean square error n

(Test − Ti )2

i

s2 =

(3)

n−2

Table II. Number of stations selected for each case studied (#) and the percentage of these stations (%) that are located within urban areas with populations greater than 10 000. Period

Recent (1970–2004)

Variable

Tmax Tmin

Early (1940–1969)

Tmax Tmin

Annual

m

Winter

Spring

Summer

Fall

#

%

#

%

#

%

#

%

#

%

Positive Negative Positive Negative

221 46 147 84

26.2 17.4 34.7 19.0

155 56 133 97

26.5 28.6 33.1 22.7

266 54 138 91

24.4 29.6 35.5 25.3

245 29 154 69

24.9 20.7 29.2 21.7

156 65 140 90

21.2 18.5 33.6 18.9

Positive Negative Positive Negative

42 128 47 118

26.2 38.3 36.2 33.9

18 150 47 107

22.2 33.3 31.9 34.6

56 58 65 84

25.0 27.6 33.8 36.9

52 86 73 99

26.9 36.0 39.7 37.4

72 65 51 78

22.2 36.9 31.4 39.7

Copyright  2008 Royal Meteorological Society

Int. J. Climatol. 29: 1324–1329 (2009) DOI: 10.1002/joc

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where Ti is the observed temperature at the ith year, an estimate of α is achieved by substituting s 2 in place of σ 2 in Equation (2). For evenly spaced data points t = (n + 1)/2 years and Equation (2) reduces to 2 α = 12s 2 /[n(n √ − 1)]. The so-called standard error of m is ε = α, and error bars at the approximately 95% confidence interval for m are given by m ± 2ε (Wigley, 2006). However, since T data are seldom free of autocorrelation, in the above formula for ε we use the effective sample size (neff < n): neff =

n(1 − |r1 |) (1 + |r1 |)

(4)

where r1 is the lag-1 autocorrelation coefficient of the observed data (the time series of residuals about the fitted straight line). The gaps in the time series (the missing years) are irrelevant for the computation of m; however for the computation of r1 , we simply set the residuals to zero at the missing years. The effect of the autocorrelation is to produce wider confidence intervals and greater uncertainty in the estimation of m. Consequently, for each of the 20 overall cases considered (two variables: Tmax , Tmin , two periods: early and recent, and five cases: four seasonal plus annual) we choose only stations with statistically significant m; i.e. 0 ∈ / [m − 2ε, m + 2ε], or in words: ‘zero is not in the closed interval [m − 2ε, m + 2ε]’. The above results in approximately 100–300 stations (depending on the case) of which most were located in non-urban areas (Table II and Figures 1–5), and for which no correlation with altitude was found.

4.

Results and discussion

A summary of our main results is given in Table III, and particular details are depicted in Figures 1–5. These

results confirm that indeed Mexico has warmed up during the recent period (1970–2004); but also that this is not an outright warming, as suggested at the beginning of this work. That is, in all ten cases considered for this period (Tmax and Tmin , for the four seasons plus annual means) there are more stations having positive statistically significant trends than negative trends (see the first two rows of Table III). Similarly, the results also show that during the early period (1940–1969) Mexico cooled down, although this cooling was even less generalized. That is, in some cases, the number of stations having negative trends is comparable to the number of stations having positive trends (see the last two rows of Table III). In general, despite the fact that we use very different criteria in selecting stations, our results seem to corroborate previous studies (Englehart and Douglas, 2004, 2005); this indicates that there is little or none urban heat-island effect in our data. Relaxing the urban-effect criterion in selecting stations allowed us to have a greater number [compared with Englehart and Douglas (2004)] of stations and thus to offer more details. For example, we found that during the recent period, warming was more generalized in Tmax than in Tmin , and in summer than in the other seasons (in summer, for Tmax , 245 out of 274 stations warmed up; see Figure 1). However, during the early period, cooling was more generalized in winter than in the other seasons (for Tmax , 150 out of 168 stations cooled down; see Figure 2); which is somewhat in disagreement with Englehart and Douglas (2005) (from their Figure 3, it seems that cooling was more generalized or widespread in their ‘warm’ – June to September–season, for both: Tmax and Tmin ). In other cases our results partially agree with Englehart and Douglas (2005). For example Tmax during spring of the recent period (Figure 3), where our results agree in the North-west region (warming); but not

32 30 28 26 24 22 20 18 16 14 −120

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Figure 1. Stations having statistically significant trends (positive: orange asterisks; negative: blue asterisks; a triangle indicates a station within an urban area) for recent period, Tmax , summer. This figure is available in colour online at www.interscience.wiley.com/ijoc Copyright  2008 Royal Meteorological Society


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32 30 28 26 24 22 20 18 16 14 −120

−115

−110

−105

−100

−95

−90

Figure 2. Same as Figure 1, but for early period, Tmax , winter. This figure is available in colour online at www.interscience.wiley.com/ijoc

32 30 28 26 24 22 20 18 16 14 −120

−115

−110

−105

−100

−95

−90

Figure 3. Same as Figure 1, but for recent period, Tmax , spring. This figure is available in colour online at www.interscience.wiley.com/ijoc

in the North-east region, where we found that the number of stations having statistically significant positive trends is four times the number of stations having negative trends and their average trend is not significant (see their Figure 3). Also Tmin during the summer of the early period (Figure 4), where the ratio of stations having statistically significant positive trends over negative (ρ) is above 0.7 (ρ = 73/99), and Englehart and Douglas (2005) report generalized cooling except for the Northeast region which is neutral. Our results show that the behaviour of North-western Mexico (NWM), which in this work we define as the Baja California peninsula plus the states of Sonora and Sinaloa, often contrasts with the rest of Mexico. For example, NWM warming tends to be much more pronounced in the recent period, that is Tmax during the spring (Figure 3) and summer Copyright  2008 Royal Meteorological Society

(Figure 1), where this region shows ρ = 55/1 for spring, and ρ = 38/2 for summer, both significantly higher than the corresponding values for the entire country: ρ = 4.9 and 8.4, respectively. A rather similar situation is observed for the case of Tmin during the winter of the recent period (Figure 5). On the other hand, during the early period, NWM cooling tends to be somewhat different than in the rest of the country, e.g. Tmax during winter (Figure 2), with ρ = 4/7 (compared to the country’s ρ = 0.1) and Tmin during summer (Figure 4), where in north-western Baja California the four stations with statistically significant trends are positive (ρ = ∞) and the rest of the country has ρ = 0.7 (NWM has ρ = 8/12). Certainly, as mentioned in the Introduction, stations are unevenly distributed, however the ρ values for NWM during the recent-period’s summer and spring Int. J. Climatol. 29: 1324–1329 (2009) DOI: 10.1002/joc

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−115

−110

−105

−100

−95

−90

Figure 4. Same as Figure 1, but for early period, Tmin , summer. This figure is available in colour online at www.interscience.wiley.com/ijoc

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Figure 5. Same as Figure 1, but for recent period, Tmin , winter. This figure is available in colour online at www.interscience.wiley.com/ijoc

(Figures 1 and 3) involve about 1/6 of the total number of stations considered for the whole country in those cases (NWM comprises about 1/5 of Mexico’s territory). It is also noteworthy that central Mexico, specifically the states of Durango and Zacatecas (around 104 ° W, 24° N), repeatedly show an opposite behaviour than the country’s overall tendency (Figures 2–4). In general, there seems to be no direct effect of ENSO on T trends over Mexico; i.e. the number of warm (El Niño) and cold (La Niña) ENSO events within both periods is almost the same (Table IV). Nevertheless it has been suggested that in this country El Niño favours warm summers during warm PDO events as well as cool winters irrespective of the PDO phase, and that La Niña favours cool summers irrespective of the PDO phase (Pavia et al., 2006). Here we found that at the beginning of the recent period, the PDO began a warming trend and that this period was marked by warm PDO years (compared to Copyright  2008 Royal Meteorological Society

both: the early period and the same period’s cold PDO); also that at the beginning of the early period, the PDO began a cooling trend and that this period was marked by cold PDO years (compared to the same period’s warm PDO), and less active than the recent period, i.e. with more neutral years: neither El Niño or La Niña, nor warm PDO or cold PDO (see Table IV). Since the main results of this work are in agreement with previous studies (e.g. Englehart and Douglas, 2004), it is important to underline its most important characteristic which differentiates it from other investigations. Data: We use an updated data-set which includes records up to 2004; and in general we use more stations than Englehart and Douglas (2004) [depending on the case, up to three times, or ∼100 to ∼300 versus ∼100]. Method: We estimate the significance of each station’s trend, selecting only those which are significant at the 95% confidence level; and the analysis is Int. J. Climatol. 29: 1324–1329 (2009) DOI: 10.1002/joc

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Table III. Ratio of number of stations with statistically significant positive trend over statistically significant negative trend (ρ). Period

Variable

Winter

Spring

Summer

Fall

Annual

Recent (1970–2004)

Tmax Tmin

2.8 1.4

4.9 1.5

8.4 2.2

2.4 1.6

4.8 1.8

Early (1940–1969)

Tmax Tmin

0.1 0.4

1.0 0.8

0.6 0.7

1.1 0.7

0.3 0.4

Table IV. Classification of years based on ENSO and PDO phases [adapted (and updated) from Table I of Pavia et al. (2006)]. Neutral years are not included. Period

El Niño

La Niña

Warm PDO

Cold PDO

Recent (1970–2004)

2003, 1992, 1983, 1973,

1998, 1995, 1988, 1987, 1978, 1977, 1970

2001, 2000, 1999, 1996, 1989, 1985, 1984, 1974, 1972, 1971

2003, 1995, 1988, 1984, 1977

1996, 1989, 1985, 1978,

2001, 2000, 1999, 1976, 1974, 1973, 1972, 1971, 1970

Early (1940–1969)

1969, 1966, 1964, 1958, 1942, 1941, 1940

1965, 1956, 1955, 1951, 1950, 1943

1943, 1942, 1941, 1940

1969, 1966, 1965, 1964, 1958, 1956, 1955, 1951, 1950

done station by station, that is without spatial averaging. Results: Mexico has warmed up during the recent period, in agreement with Englehart and Douglas (2005) [during the recent period warming was more generalized in Tmax than in Tmin , and in summer than in the other seasons (Table III)], but we offer more details on this warming (Figures 1, 3 and 5). And, in contrast with Englehart and Douglas (2005), we show that during the early period cooling was more generalized in winter than in the other seasons (Table III and Figure 2). Furthermore, this work allowed us to highlight the fact that north-western and central Mexico often contrasts with the rest of the country (Figures 1–5). In addition we find that there are no direct effects of ENSO on either the cooling down of the early period or the warming up of the recent period. In contrast we found that there were more cold PDO years than warm PDO years in the former, and a cooling PDO trend at the beginning of the period; as well as more warm PDO years than cold PDO years in the latter, and also a warming PDO trend at the beginning of the period (Table IV).

5.

Conclusions

This paper represents an updated revision of temperature trends in Mexico, which confirm a recent country-wide warming tendency independent of ENSO, yet consistent with PDO behaviour. We believe that this corroboration, using a more robust statistical method, represents an important finding which, in addition to the series of station-by-station details offered in Figures 1–5, tally up

Copyright  2008 Royal Meteorological Society

1998, 1992, 1987, 1983,

to compose a key contribution to the study of Mexico’s climate. Acknowledgements This research was funded by the Mexican CONACYT system. We thank the Mexican water authority for providing us with the climatological data, and two anonymous referees for helpful reviews. References Brohan P, Kennedy J, Harris I, Tett SFB, Jones PD. 2006. Uncertainty estimates in regional and global observed temperature changes: new dataset from 1850. Journal of Geophysical Research 111: D12106, DOI:10.1029/2005JD006548. Englehart PJ, Douglas AV. 2004. Characterizing regional-scale monthly and seasonal temperature variations over Mexico. International Journal of Climatology 24: 1897–1909, DOI: 10.1002/joc.1117. Englehart PJ, Douglas AV. 2005. Changing behavior in the diurnal range of surface air temperatures over Mexico. Geophysical Research Letters 32: L01701, DOI: 10.1029/2004GL021139. IPCC. 2007. In Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, Solomon S, Qin D, Manning M, Chen Z, Marquis M, Averyt KB, Tignor M, Miller HL (eds). Cambridge University Press: Cambridge, New York; 996. Jones PD. 1994. Hemispheric surface air temperature variations: a reanalysis and an update to 1993. Journal of Climate 7: 1794–1802. Liverman DM, O’Brien KL. 1991. Global warming and climate change in Mexico. Global Environmental Change 1: 351–364. Pavia EG, Graef F, Reyes J. 2006. PDO-ENSO effects in the climate of Mexico. Journal of Climate 19: 6433–6438. Wigley TML. 2006. Statistical issues regarding trends. In Temperature Trends in the Lower Atmosphere: Steps for Understanding and Reconciling Differences, Karl TR, Hassol SJ, Miller CD, Murray WL (eds). Climate Change Scientific Program: Washington, DC; 164.
