Maximum and minimum temperature trends for the globe: An update through 2004

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1 GEOPHYSICAL RESEARCH LETTERS, VOL. 32, L23822, doi: /2005gl024379, 2005 Maximum and minimum temperature trends for the globe: An update through 2004 Russell S. Vose, David R. Easterling, and Byron Gleason National Climatic Data Center, Asheville, North Carolina, USA Received 11 August 2005; revised 11 October 2005; accepted 26 October 2005; published 14 December [1] New data acquisitions are used to examine recent global trends in maximum temperature, minimum temperature, and the diurnal temperature range (DTR). On average, the analysis covers the equivalent of 71% of the total global land area, 17% more than in previous studies. Consistent with the IPCC Third Assessment Report, minimum temperature increased more rapidly than maximum temperature (0.204 vs C dec 1 ) from , resulting in a significant DTR decrease ( C dec 1 ). In contrast, there were comparable increases in minimum and maximum temperature (0.295 vs C dec 1 ) from , muting recent DTR trends ( C dec 1 ). Minimum and maximum temperature increased in almost all parts of the globe during both periods, whereas a widespread decrease in the DTR was only evident from Citation: Vose, R. S., D. R. Easterling, and B. Gleason (2005), Maximum and minimum temperature trends for the globe: An update through 2004, Geophys. Res. Lett., 32, L23822, doi: / 2005GL Introduction [2] Minimum temperature increased about twice as fast as maximum temperature over global land areas since 1950, resulting in a broad decline in the diurnal temperature range (DTR [Folland et al., 2001]). Changes in cloud cover, precipitation, soil moisture, and atmospheric circulation likely accounted for much of the trend differential during the period [e.g., Dai et al., 1999; Przybylak, 2000; Braganza et al., 2004]. Changes in land use also impacted the DTR in some areas [e.g., Balling et al., 1998; Bonan, 2001; Small et al., 2001]. Unfortunately, data constraints have historically limited global-scale analyses of DTR trends and their causes; in particular, the most recent global assessment [Easterling et al., 1997] only covered about half of the land surface and ended in Consequently, in this study we use new data acquisitions to expand spatial coverage and update global trends in maximum temperature, minimum temperature, and the DTR through the period For consistency with the IPCC Fourth Assessment Report, trends during the satellite era ( ) are also discussed. 2. Data [3] Data for this study were compiled from 20 source datasets. The primary sources were the Global Historical This paper is not subject to U.S. copyright. Published in 2005 by the American Geophysical Union. Climatology Network [Peterson and Vose, 1997] monthly and daily databases (which contain most of the data used by Easterling et al.), and two editions of World Weather Records ( and ). These global datasets were supplemented with acquisitions from Argentina, Australia, Brazil, Chile, Cuba, Greece, Iran, New Zealand, and South Africa. CLIMAT reports were used to update about 20% of the stations after In addition, highquality synoptic reports were included to fill recent gaps in about 10% of the stations (provided digital and manual checks indicated that the synoptic data closely matched historical monthly time series during periods of overlaps). [4] The source data were quality assured using methods described by Peterson et al. [1998]. In brief, this involved identifying and merging duplicates, deleting stations with extreme changes in the mean and/or variance, and removing temporal and spatial outliers. The final, quality-assured dataset contained 7018 maximum and 6970 minimum temperature stations that had at least 20 years of complete data (i.e., 8 months per year). The DTR time series for each station was created by subtracting the minimum series from the maximum series. [5] The approach of Menne and Williams [2005] was then employed to produce adjustments for undocumented changes in station location, instrumentation, and observing practice. The first step entailed locating each station s six nearest neighbors and then compositing their annual anomalies into a reference series that represented the presumed homogeneous regional climate signal. Next, the reference series was subtracted from the candidate series, and the resulting difference series was checked for potential change points using two-phase regression and the Standard Normal Homogeneity Test. When both tests found a change point within two years of one another, an adjustment was applied to the candidate series. [6] Unlike Easterling et al. [1997], the final adjusted dataset was not stratified into urban and rural subnetworks because urban warming does not appear to significantly bias multidecadal trends over large areas. For example, Jones et al. [1990] found that the impact of urbanization was roughly an order of magnitude smaller than the trend in mean temperature over global land areas during most of the 20th century. Easterling et al. [1997] also noted that urban effects on global and hemispheric trends in maximum and minimum temperature and the DTR were negligible for the period Peterson et al. [1999] obtained only a slightly smaller global trend for a rural station network than for a blended rural-urban network over the period , the difference being statistically insignificant. More recently, Parker [2004] found that calm nights, which should in theory experience greater urban effects, had the same L of5

2 global DTR trends for differ by only C dec 1 ). A total of 3588 maximum, 3565 minimum, and 3360 DTR stations each have at least 21 years of data during the satellite period. On average, the resulting dataset covers the equivalent of 71% of the land surface. Coverage exceeds 70% from , dropping to 62% in 2003 and 48% in Figure 1. Time series of annual maximum temperature, minimum temperature, and DTR anomalies for global land areas over the period increases in minimum temperature as did windy nights for the period Methods [7] The climate anomaly method [Jones and Moberg, 2003] was used to develop global, hemispheric, and gridbox time series for the period The first step involved excluding stations that had less than 21 years of data during a base period of and less than 4 years of data in each decade during that 30-year span. Base-period normals were then computed by month for the remaining 4280 maximum, 4284 minimum, and 4157 DTR stations. Next, each monthly temperature at each station was converted to an anomaly from its base-period mean. The station-based anomalies were then averaged into 5 by 5 latitude-longitude grid boxes for each year/month from Finally, global and hemispheric means were computed by area-weighting each grid box by the cosine of the central latitude and averaging all of the weighted gridbox values in the given year/month. On average, the resulting dataset covers the equivalent of 71% of the total global land area, 17% more than in previous studies. Coverage exceeds 70% for all years during the base period, with a gradual decrease toward both ends of the record (to 54% by 1950 and 42% by 2004). Although sampling is relatively complete across the mid-latitudes, the tropical and polar land masses remain underrepresented because of a comparative lack of data. [8] The climate anomaly method was also used to develop global, hemispheric, and grid-box time series for the satellite era. To maximize spatial coverage, a base period of was used instead of because the latter results in grid-box trend maps that cover 12% less of the land surface. (In general, the two base periods yield comparable results at large spatial scales; for instance, their Trends [9] Figure 1 depicts the global annual time series for each variable for the period In general, both maximum and minimum temperature increase from about the mid-1970s to present, with warming in the minimum during the 1950s as well. The DTR generally decreases during the period, though much of the change occurs in two periods (the 1950s and the early-1970s to early 1980s). From , the maximum temperature trend is C dec 1,the minimum temperature trend is C dec 1, and the DTR trend is C dec 1 (all trends computed via leastsquares regression). The maximum and minimum trends exceed those in Easterling et al. [1997] by and C dec 1, respectively, whereas the DTR trend is less by C dec 1. The larger maximum and minimum trends are generally consistent with the large positive global temperature anomalies observed in most years since 1993 [Levinson et al., 2005] while the smaller DTR trend likely reflects the accelerated rate of warming in the maximum. (Note that the DTR change does not appear to stem from differences in data coverage because the current dataset produces the same DTR trend as in Easterling et al. for the period ) In general, the trends for all variables are larger in the Northern Hemisphere, with the greatest warming in the boreal winter and spring (Table 1). Relatively speaking, trends exhibit little seasonality in the Southern Hemisphere. Table 1. Annual and Seasonal Trends ( C dec 1 ) From for Maximum Temperature, Minimum Temperature, and the DTR for Global Land Areas and the Northern and Southern Hemispheres a Season Maximum Minimum DTR Globe Annual D-J-F M-A-M J-J-A S-O-N Northern Hemisphere Annual D-J-F M-A-M J-J-A S-O-N Southern Hemisphere Annual D-J-F M-A-M J-J-A S-O-N a Values in bold are not significant at the 5% level. 2of5

3 Figure 3. Time series of annual maximum temperature, minimum temperature, and DTR anomalies for global land areas over the period increase in South Korea was first discussed by Jung et al. [2002]. In addition, Rusticucci and Barrucand [2004] detected a decrease in maximum temperature in northern Argentina as well as an increase in minimum temperature in much of the country. Figure 2. Least-squares trends in 5 by 5 grid boxes for annual maximum temperature, minimum temperature, and DTR anomalies for the period [10] Figure 2 depicts the annual trend for each variable in each 5 by 5 grid box during the period Boxes having less than 37 years of data (67% completeness) were excluded from the analysis. Maximum temperature increased in most regions except northern Mexico and northern Argentina, both of which cooled during the 55-year period. There was little net change in maximum temperature in northeastern Canada, the southeastern United States, and southern China. Minimum temperature increased in virtually all areas except Mexico, northeastern Canada, and parts of the western Pacific Ocean. The DTR generally declined in most areas, although the pattern was less spatially coherent than for its components, and increases were apparent in some regions (e.g., northeastern Canada, southern Argentina, eastern Africa, the western Pacific Ocean, southeastern Australia). [11] These findings are in general agreement with a number of recent regional-scale analyses. For instance, increases in maximum and minimum temperature and decreases in the DTR during the latter half of the 20th century have been independently documented for Alaska [Stafford et al., 2000], the Arctic in general [Tuomenvirta et al., 2000], Poland [Wibig and Glowicki, 2002], and South Africa [Kruger and Shongwe, 2004]. The lack of a DTR decline over parts of Canada since 1950 was previously noted by Bonsal et al. [2001], while a DTR Trends [12] Figure 3 depicts the global annual time series for each variable for the period In general, maximum and minimum temperature increase through most of the period whereas the DTR is basically trendless. The Table 2. Annual and Seasonal Trends ( C dec 1 ) From for Maximum Temperature, Minimum Temperature, and the DTR for Global Land Areas and the Northern and Southern Hemispheres a Season Maximum Minimum DTR Globe Annual D-J-F M-A-M J-J-A S-O-N Northern Hemisphere Annual D-J-F M-A-M J-J-A S-O-N Southern Hemisphere Annual D-J-F M-A-M J-J-A S-O-N a Values in bold are not significant at the 5% level. 3of5

4 the north Pacific Ocean. Minimum temperature increased in virtually all areas except southern Argentina, western Australia, and parts of the western Pacific Ocean. The DTR pattern was far less consistent, with increases in some areas (e.g., western North America, northern Eurasia, the Indian subcontinent, Australia) and decreases in others (e.g., northeastern Canada, the southeastern United States, Africa, parts of central and eastern Asia). 6. Summary and Conclusions [14] In this study we used a suite of new data acquisitions to examine recent global trends in maximum temperature, minimum temperature, and the DTR. Consistent with Easterling et al. [1997], minimum temperature increased at a faster rate than maximum temperature during the latter half of the 20th century, resulting in a significant decrease in the DTR for this period. In contrast, maximum and minimum temperature increases were roughly comparable during the satellite era, muting recent changes in the DTR. Maximum and minimum temperature increased in almost all parts of the globe during both periods, whereas a widespread decrease in the DTR was only evident from [15] Acknowledgments. The authors thank Tom Peterson, Phil Jones, and the anonymous reviewers for their insightful comments and suggestions on this article. Partial support for this work was provided by the Office of Biological and Environmental Research, U.S. Department of Energy (Grant number DE-AI02-96ER62276); and the NOAA Office of Global Programs, Climate Change Data and Detection Element. Figure 4. Least-squares trends in 5 by 5 grid boxes for annual maximum temperature, minimum temperature, and DTR anomalies over the period maximum and minimum temperature trends are nearly identical (0.287 versus C dec 1 ), and both are comparable to the mean temperature trend over global land areas for the period (0.296 C dec 1 ) as derived from the Global Historical Climatology Network database (J. Lawrimore, personal communication, 2005). Given the similarity between maximum and minimum temperature, the trend in the DTR ( C dec 1 ) is not statistically significant at the 5% level. Although striking, the lack of a DTR trend is not without precedent (e.g., there was no trend from either). Furthermore, the DTR does exhibit a significant decrease ( C dec 1 ) since 1976, which Folland et al. [2001] defined as the start of the most recent warming period. On average, trends in maximum and minimum temperature are larger in the Northern Hemisphere, and both hemispheres have more warming in winter and spring (Table 2). A DTR increase is evident in the Southern Hemisphere winter (mainly in Australia), but all other DTR changes are insignificant. [13] Figure 4 depicts the annual trend for each variable in each 5 by 5 grid box during the period Boxes having less than 21 years of data (80% completeness) were excluded from the analysis. In general, maximum temperature increased in most regions except northern Peru, northern Argentina, northwestern Australia, and parts of References Balling, R. C., Jr., J. M. Klopatek, M. L. Hildebrandt, C. K. Moritz, and C. J. Watts (1998), Impacts of land degradation on historical temperature records from the Sonoran Desert, Clim. Change, 40, Bonan, G. B. (2001), Observational evidence for reduction of daily maximum temperature by croplands in the midwest United States, J. Clim., 14, Bonsal, B. R., X. Zhang, L. A. Vincent, and W. D. Hogg (2001), Characteristics of daily and extreme temperatures over Canada, J. Clim., 14, Braganza, K., D. J. Karoly, and J. M. Arblaster (2004), Diurnal temperature range as an index of global climate change during the twentieth century, Geophys. Res. Lett., 31, L13217, doi: /2004gl Dai, A., K. E. Trenberth, and T. R. Karl (1999), Effects of clouds, soil moisture, precipitation, and water vapor on diurnal temperature range, J. Clim., 12, Easterling, D. R., et al. (1997), Maximum and minimum temperature trends for the globe, Science, 277, Folland, C. K., et al. (2001), Observed climate variability and change, in Climate Change 2001: The Scientific Basis, pp , Cambridge Univ. Press, New York. Jones, P. D., and A. Moberg (2003), Hemispheric and large-scale surface air temperature variations: An extensive revision and an update to 2001, J. Clim., 16, Jones, P. D., P. Y. Groisman, M. Coughlin, N. Plummer, W. C. Wang, and T. R. Karl (1990), Assessment of urbanization effects in time series of surface air temperature over land, Nature, 347, Jung, H.-S., Y. Choi, J.-H. Oh, and G.-H. Lim (2002), Recent trends in temperature and precipitation over South Korea, Int. J. Climatol., 22, Kruger, A. C., and S. Shongwe (2004), Temperature trends in South Africa: , Int. J. Climatol., 24, Levinson, D. H., et al. (2005), State of the climate in 2004, Bull. Am. Meteorol. Soc., 86, S1 S86. Menne, M. J., and C. W. Williams Jr. (2005), Detection of undocumented change points: On the use of multiple test statistics and composite reference series, J. Clim., 18, Parker, D. E. (2004), Large-scale warming is not urban, Nature, 432, 290. Peterson, T. C., and R. S. Vose (1997), An overview of the Global Historical Climatology Network temperature database, Bull. Am. Meteorol. Soc., 78, of5

5 Peterson, T. C., R. S. Vose, V. N. Razuvaev, and R. L. Schmoyer (1998), Global Historical Climatology Network (GHCN) quality control of monthly temperature data, Int. J. Climatol., 18, Peterson,T.C.,K.Gallo,J.Lawrimore,T.Owen,A.Huang,andD. McKittrick (1999), Global rural temperature trends, Geophys. Res. Lett., 26, Przybylak, R. (2000), Diurnal temperature range in the Arctic and its relation to hemispheric and Arctic circulation patterns, Int. J. Climatol., 20, Rusticucci, M., and M. Barrucand (2004), Observed trends and changes in temperature extremes over Argentina, J. Clim., 17, Small, E. E., L. C. Sloan, and R. Nychka (2001), Changes in surface air temperature caused by desiccation of the Aral Sea, J. Clim., 14, Stafford, J. M., G. Wendler, and J. Curtis (2000), Temperature and precipitation of Alaska: 50 year trend analysis, Theor. Appl. Climatol., 67, Tuomenvirta, R. H., H. Alexandersson, A. Drebs, P. Frich, and P. O. Nordli (2000), Trends in Nordic and Arctic temperature extremes, J. Clim., 13, Wibig, J., and B. Glowicki (2002), Trends of minimum and maximum temperature in Poland, Clim. Res., 20, D. R. Easterling, B. Gleason, and R. S. Vose, National Climatic Data Center, 151 Patton Avenue, Asheville, NC 28801, USA. noaa.gov) 5of5

Comparison of Global Mean Temperature Series

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