4.1. Hemispheric-Scale Averages and Comparisons With CRUTEM3
 Hemispheric-average time series were produced using cosine weighting of grid-box values in each hemisphere [Jones, 1994]. Averages were calculated for each month from January 1850, and then seasonal and annual averages were calculated using the hemispheric-average monthly values. Standard 3 month climatological seasons were used, with December of the previous year counting toward the winter value for the current year. As December 1849 is not available, all the seasonal and annual series for the Northern Hemisphere (NH) begin in 1851. For the Southern Hemisphere (SH), the first year is taken as 1856. Before this date, there are fewer than 5 stations with data. Beginning with 1856, the number of available stations in the SH increases to 5 series, reaching 10 by 1860 (see Figure 1). In later figures (Figures 5b5 and 9b) we will highlight that uncertainty ranges of SH averages, calculated from so few stations, are substantial.
 Figure 222 shows the seasonal and annual values for the NH and SH and an annual series for the global land together with 10 year Gaussian smoothed series. For comparison, the smoothed CRUTEM3 series are also shown to indicate the impact of the additional or replaced series in the station database. The global land series is computed by weighting the two hemispheres approximately in proportion to the areas of their landmasses (i.e., global = [(2/3)NH + (1/3)SH]). This weighting is different from the equal hemispheric weighting applied by Brohan et al.  for CRUTEM3. The new weighting has also been applied here to CRUTEM3.
Figure 2. Seasonal and annual averages by hemisphere for CRUTEM4, with the smoothed lines showing decadal-filtered series for CRUTEM4 (thick) and CRUTEM3 (thin). Hemispheric temperature averages for the land areas are expressed as anomalies (in degrees Celsius from the base period of 1961–1990). The decadal smoothing uses a 13-term Gaussian filter, padded at the ends with the mean of the adjacent 6 values. (a) NH, (b) SH and (c) global for the annual average. The global average is calculated as [(2/3)NH + (1/3)SH].
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 The differences between the two sets of smoothed lines indicate excellent agreement from 1880 up to 2000 for the NH. At this decadal time scale, all the additions have made no discernible differences between the analyses, an initial indicator that for hemispheric-scale averages the analysis is very robust. CRUTEM4 is very slightly warmer since 2000 for the NH for the year and all seasons except summer. The likely reason for this is the additional data in the Arctic (particularly Russia), and this is further investigated in the next section. Prior to 1880, CRUTEM4 is slightly cooler than CRUTEM3, more so in winter (December, January, and February (DJF)) and spring (March, April, and May (MAM)) than in the other seasons. Again, later analyses will be suggestive that this results from the additional Russian series. For the SH, differences between CRUTEM4 and CRUTEM3 are slightly greater earlier in the series and extend up to the early 20th century, particularly in the austral winter (June, July, and August (JJA)). CRUTEM4 is cooler than CRUTEM3 during 1861–1910, the exact period depending on the season. CRUTEM4 has been very slightly warmer than CRUTEM3 since about 2005. Possible reasons for the differences in the 19th century in the SH are investigated in the next section. Uncertainty ranges, calculated using the same approach as that used by Brohan et al.  are shown in later figures (on the decadal scale in Figure 5 and on the interannual time scale in Figure 9).
 For the NH, year-to-year variability is greatest during winter and least in summer. The slightly greater variability prior to 1880 in all seasons (except summer) is more likely to be due to sparser coverage then a real feature. This greater variability is marginally reduced by adjusting the individual grid-box time series for changing station data contributions (introduced by Jones et al.  and the data set produced here called CRUTEM4v), but the variance of regional averages has not been similarly adjusted for reduced grid-box availability. For the SH, year-to-year variability is more similar between the seasons.
 All seasons and the annual series for both hemispheres show comparable century-scale warming from the beginning of the 20th century, but there are differences in timing between them. Warming is significant in all seasons and annually for 1861–2010, 1901–2010, and 1979–2010 (except for May and December for the SH for 1979–2010). Table 2 provides the warming explained by a least squares linear fit to the monthly series for these three periods. Warming in all three periods tends to be greater in the NH compared with that in the SH, and the NH warming has a much more marked seasonal character than that for the SH. Table 2 also includes calendar year average values for CRUTEM3. CRUTEM4 warms more than CRUTEM3 for all three periods because of the cooler values before about 1880 (particularly in the SH) and slightly warmer values in the NH since about 2000.
Table 2. Total Temperature Change (°C) for CRUTEM4 Described by Linear Least Squares Regression Lines Fitted Over Three Periods: 1861–2010, 1901–2010, and 1979–2010a
 The marked seasonality of the warming for 1861 to ∼1900 (estimated by comparing the NH trend differences in Table 2 for 1861–2010 and 1901–2010) may be artificial because of the possible impacts of direct sunlight on the instruments prior to the development of Stevenson-type screens in higher northern latitudes during summer (see earlier discussion in relation to the HISTALP data set [Böhm et al., 2010]). The addition of the newly adjusted series in the GAR may be the reason for the slight difference between CRUTEM3 and CRUTEM4 before 1860, when coverage was sparse outside Europe. Böhm et al.  and Brunet et al.  suggested that this issue is much wider in scale across the midlatitudes and high latitudes of the NH. Alternatively, if this seasonal contrast is real, then it implies a marked change in continentality (greater winter-summer temperature differences) over part of the NH prior to 1880. Further work is required, but the studies reported above are clearly suggestive of screen exposures being the more likely cause.
 In this section we compare spatial patterns between CRUTEM4 and the earlier CRUTEM3 data set. In Figure 3, we plot the annual temperature anomaly for the decade 2001–2010, with respect to our base period of 1961–1990, for both analyses and their difference. This difference clearly illustrates the improvement (i.e., outlined in black in Figure 3c) in coverage in CRUTEM4 compared with CRUTEM3, particularly across the higher latitudes of Eurasia and North America. As this expansion of spatial coverage in the Northern Hemisphere has contributed to warmer temperatures in CRUTEM4, the 2001–2010 decade is warmer than in CRUTEM3 for the NH (0.80°C compared with 0.73°C). There is much less coverage change across the Southern Hemisphere, and the two corresponding averages are 0.43°C for CRUTEM4 and 0.40°C for CRUTEM3. Figure 3c is mostly green, but differences do occur, particularly over the contiguous United States and Australia, where we have made many changes to the station data used (see discussion in section 2).
Figure 3. Comparison of annual mean temperature anomalies from (a) CRUTEM3 and (b) CRUTEM4 for the period 2001–2010 (degC anomalies from 1961 to 1990). Grid boxes with less than 50% data coverage (5 years) are left white. (c) Difference between Figures 3b and 3a to compare CRUTEM3 and CRUTEM4 means over this period. Grid boxes with insufficient data (<5 years during 2001–2010) in CRUTEM3 but sufficient data in CRUTEM4 are outlined in black; black crosses indicate the reverse situation.
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 In Figure 4, we show linear trend maps for annual temperature averages for 1951–2010 for both analyses and the difference. Figure 4b for CRUTEM4 shows the improvements in coverage, which can also be seen in Figure 4c by the grid boxes outlined in black. Of the grid boxes in common between the two analyses, 499 boxes differ within ±0.2°C in their total trends over the 60 year period, with 86 boxes indicating that the CRUTEM4 trend was >0.2°C more than CRUTEM3 and 41 with CRUTEM3 having >0.2°C more warming than CRUTEM4.
Figure 4. Comparison of linear trends fitted to (a) CRUTEM3 and (b) CRUTEM4 annual temperatures for the period 1951–2010. Trends are expressed as the degC linear trend change over the 60 year period. Grid boxes with less than 80% data coverage (48 years) are left white. Boxes or regions outlined in black are those where the trend slopes are significantly different from zero, with 95% confidence taking into account first-order autocorrelation. (c) Difference between Figures 4b and 4a to compare CRUTEM3 and CRUTEM4 trends over this period. Grid boxes with insufficient data (<48 years during 1951–2010) in CRUTEM3 but sufficient data in CRUTEM4 are outlined in black; black crosses indicate the reverse situation.
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4.3. Comparison of Annual Hemispheric Series With the Results of Analyses by Other Groups
 In this section the two hemispheric land-only averages are compared with two other analyses: the series developed by the National Climatic Data Center (NCDC) [Smith et al., 2008] and the Goddard Institute for Space Studies (GISS) [Hansen et al., 2010]. Our present study uses a base period of 1961–1990, while NCDC currently uses 1901–2000 and GISS uses 1951–1980 for their published series. For direct comparison we have adjusted both series to our 1961–1990 base period on a monthly basis. Figure 99 shows hemispheric seasonal and annual series from CRUTEM4, additionally plotting decadally smoothed series for the two U.S. analyses. For both the NH and SH, CRUTEM4 tends to more closely follow NCDC than it does GISS, even though all three show similar amounts of long-term warming since 1880. The reason why CRUTEM4 more closely follows NCDC has been discussed before [Vose et al., 2005] and relates to these two analyses using the same 5° × 5° latitude-longitude grid boxes compared with the 40 equal-area boxes used per hemisphere by GISS. Correlations between CRUTEM4 and NCDC-GISS are 0.984/0.980 for the NH and 0.950/0.927 for the SH (for the 1880 to 2010 period) and support the findings of Vose et al. . Differences among the three analyses are greater in the SH compared with those of the NH, particularly before about 1920. Differences are not sustained right back to the start of records, however, as the lines move closer together again in the 1880s. The uncertainty ranges for the SH are larger than those of the NH because of more missing boxes (particularly over the Antarctic) and fewer stations per grid box over Africa and South America than the northern continents.
4.4. Comparisons With ERA-Interim and ERA-40 Reanalyses
 In this section we compare CRUTEM4 at the hemispheric resolution with similar land averages calculated from two versions of the European Centre for Medium-Range Weather Forecasting (ECMWF) Re-Analyses (ERA-40 and ERA-Interim). ERA-40 covers the period 1958–2001, and ERA-Interim (which uses four-dimensional (4D) variational assimilation compared with the three-dimensional (3D) schemes in ERA-40) covers the period from 1979 to 2010. For a discussion of the ECMWF Re-Analyses see the works by Simmons et al. [2004, 2010] and Uppala et al. . A common period for both reanalyses is 1981–2000, so we reduce their absolute land temperature values to anomalies from this base period. Figure 10a10 shows seasonal and annual comparisons between the two reanalyses and CRUTEM4. As with the earlier plots, we show seasonal and annual values of CRUTEM4 (from the 1961–1990 base period) with the two ECMWF Re-Analyses as smoothed series using a 10 year Gaussian smoother. For the NH, both ERA-40 and ERA-Interim track one another very well over their period of overlap (1979–2001) and are offset from CRUTEM4 by an amount that relates to the difference between the 1961–1990 and 1981–2000 periods. In Figure 11 we compare ERA-Interim with CRUTEM4 for the Northern Hemisphere on the monthly time scale from 1979. For this plot, the base period of 1979–2010 is used for both series. The agreement between the two series is excellent. ERA-Interim warms slightly more than CRUTEM4 over this period, which is probably due to greater warming in the Arctic land grid boxes in ERA-Interim that are missing in CRUTEM4.
Figure 10. Seasonal and annual averages for CRUTEM4 compared to two versions of the ECMWF Reanalyses (red ERA-40 from 1958 to 2001 and blue ERA-Interim from 1979 to 2010). The two reanalyses have been set to a base period of 1981–2000, so are offset slightly cooler than CRUTEM4, which uses a base period of 1961–1990. Smoothing as in Figure 2. (a) NH and (b) SH.
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Figure 11. Monthly time series for ERA-Interim and CRUTEM4 (both set as anomalies by month based on the period 1979–2010) for the NH. The smoothed line is a 12-term Gaussian filter. The least squares linear trend during the 1979–2010 overlap period (using annual averages) is shown for both series, together with its slope.
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 For the SH in Figure 10b, there are marked differences between both reanalyses during their overlap period. ERA-Interim is closer to CRUTEM4, but the similarity of the smooth curves is markedly less good, particularly in the austral autumn (MAM) and winter (JJA). ERA-40 is further offset from CRUTEM4 before about 1980 in all seasons except austral summer, and this is due to a cold bias in the climate model used by both reanalyses over the Antarctic [Uppala et al., 2005]. To illustrate this further, we have calculated averages for both the SH 0º–60°S and for the Antarctic (60°S–90°S) for all three series (Figure 1212). For ERA-Interim, the time series agreement (for the SH 0°–60°S) is almost as good as the NH land, but for ERA-40, there is a significant divergence before the early 1970s, with warmer ERA-40 temperatures in all seasons. This difference was commented on by Simmons et al.  and was shown to be due to ERA-40 being given little input data for Australia prior to the early 1970s. With little input data to correct model biases, the reanalyses tend to the model simulation, which for Australia is a model that is biased warm (see further discussions by Simmons et al.  and Uppala et al. ). For the Antarctic, the cold bias in the climate model used by ERA-40 is clearly evident, particularly so in all seasons, although it is smaller in the austral summer (DJF). Figure 13 repeats Figure 11 but for the SH 0°–60°S, showing good agreement between CRUTEM4 and ERA-Interim, but this is less good than the NH for the 12 month Gaussian smoothed lines.