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GISS Surface Temperature Analysis

Global Temperature Trends: 2005 Summation

The highest global surface temperature in more than a century of instrumental data was recorded in the 2005 calendar year in the GISS annual analysis. However, the error bar on the data implies that 2005 is practically in a dead heat with 1998, the warmest previous year.

Figure 1: See caption below

Figure 1: (Left) Global annual surface temperature relative to 1951-1980 mean based on surface air measurements at meteorological stations and ship and satellite measurements for sea surface temperature. Error bars are estimated 2σ (95% confidence) uncertainty. (Right) Temperature anomaly for 2005 calendar year. Gray areas indicate a lack of station data within 1200km. (Click for a large GIF or PDF of this figure.)

Our analysis, summarized in Figure 1 above, uses documented procedures for data over land (1), satellite measurements of sea surface temperature since 1982 (2), and a ship-based analysis for earlier years (3). Our estimated error (2σ, 95% confidence) in comparing nearby years, such as 1998 and 2005, increases from 0.05°C in recent years to 0.1°C at the beginning of the 20th century. Error sources include incomplete station coverage, quantified by sampling a model-generated data set with realistic variability at actual station locations, and partly subjective estimates of data quality problems (4).

Figure 2: See caption below

Figure 2. Temperature index change since 1950 at seasonal resolution, for the globe (above) and for low latitudes. This is an update of Figure 10 in reference 4. Blue semi-circles mark La Niñas, red rectangles mark El Niños, and green triangles mark large volcanoes. (Click for a large GIF or PDF of this figure.)

Figure 3: See caption below

Figure 3. Seasonal temperature change over the past 50 years based on local linear trends. (Click for a large GIF or PDF of this figure.)

Record warmth in 2005 is notable, because global temperature has not received any boost from a tropical El Niño this year. The prior record year, 1998, on the contrary, was lifted 0.2°C above the trend line by the strongest El Niño of the past century.

Global warming is now 0.6°C in the past three decades and 0.8°C in the past century. It is no longer correct to say that "most global warming occurred before 1940". More specifically, there was slow global warming, with large fluctuations, over the century up to 1975 and subsequent rapid warming of almost 0.2°C per decade.

Recent warming coincides with rapid growth of human-made greenhouse gases. Climate models show that the rate of warming is consistent with expectations (5). The observed rapid warming thus gives urgency to discussions about how to slow greenhouse gas emissions (6).

The map shows that current warmth is nearly ubiquitous and largest at high latitudes in the Northern Hemisphere. Our ranking of 2005 as warmer than 1998 is a result mainly of the large positive Arctic anomaly. Excluding the region north of 75N, 1998 is warmer than 2005. If the entire Arctic Ocean were excluded, the ranking of 2005 may be even lower.

Our analysis differs from others by including estimated temperatures up to 1200 km from the nearest measurement station (7). The resulting spatial extrapolations and interpolations are accurate for temperature anomalies at seasonal and longer time scales at middle and high latitudes, where the spatial scale of anomalies is set by Rossby waves (7). Thus we believe that the remarkable Arctic warmth of 2005 is real, and the inclusion of estimated arctic temperatures is the primary reason for our rank of 2005 as the warmest year. Other characteristics of our analysis method are summarized in footnote (8).

Figure 2 shows the temperature index at seasonal resolution for the globe and for low latitudes (23.6°N - 23.6°S). The low latitude temperature displays clearly the occurrence of substantial El Niños, especially the prominent 1969, 1972-3,1983 and 1998 El Niños. The quasi-regularity of recent El Niños at intervals of about 4 years (there was a weak El Niño in 2002) suggests the likelihood of an El Niño in 2006 or at latest 2007. In such a case the 2005 global temperature record will almost surely be broken.

Figure 3 shows the annual and seasonal temperature changes of the past 50 years. Largest warmings have occurred in Alaska, Siberia and the Antarctic Peninsula. Most ocean areas have warmed. The remote location of most warming makes it clear that the warming is not a product of local urban influence.

References and Notes

  1. Hansen, J.E., R. Ruedy, Mki. Sato, M. Imhoff, W. Lawrence, D. Easterling, T. Peterson, and T. Karl 2001. A closer look at United States and global surface temperature change. J. Geophys. Res. 106, 23947-23963, doi:10.1029/2001JD000354.
  2. Reynolds, R.W., and T.M. Smith 1994. Improved global sea surface temperature analyses using optimum interpolation. J. Climate 7, 929-948, doi:10.1175/1520-0442(1994)007<0929:IGSSTA>2.0.CO;2.
  3. Rayner, N.A., D.E. Parker, E.B. Horton, C.K. Folland, L.V. Alexander, D.P. Rowell, E.C. Kent, and A. Kaplan 2003. Global analyses of sea surface temperature, sea ice, and night marine air temperature since the late nineteenth century. J. Geophys. Res. 108, 4407, doi:10.1029/2002JD002670.
  4. Hansen, J., R. Ruedy, J. Glascoe, and Mki. Sato 1999. GISS analysis of surface temperature change. J. Geophys. Res. 104, 30997-31022, doi:10.1029/1999JD900835.
  5. Intergovernmental Panel on Climate Change (IPCC), Climate Change 2001: The Scientific Basis, J.T. Houghton et al., Eds. (Cambridge Univ. Press, New York, 2001).
  6. Hansen, J. 2005. Is There Still Time to Avoid "Dangerous Anthropogenic Interference" with Global Climate? A Tribute to Charles David Keeling. Presentation given Dec. 6, 2005, at the American Geophysical Union, San Francisco.
  7. Hansen, J.E., and S. Lebedeff 1987. Global trends of measured surface air temperature. J. Geophys. Res. 92, 13345-13372.
  8. Analyses of global temperature change by different groups, particularly, ours (NASA GISS), the NOAA National Climate Data Center (NCDC), and the combination of the British Meteorological Office and the University of East Anglia (BMO/UEA), are generally in close agreement, as shown, e.g., in reference 5. The ranking of individual years, however, depends upon differences of only a few hundredths of a degree, which is finer than the accuracy that any method can achieve given observational limitations.
      One large source of differences is the attempt in the GISS method to estimate the temperature anomaly for all areas that have at least one station located within 1200 km, using weights for these stations that decrease linearly with distance from the station. At any given point the temperature anomaly estimated in this way can be substantially in error, but the increased coverage usually allows an improved estimate of the global temperature anomaly, as judged from tests made with spatially and temporally complete data sets generated by a general circulation model. However, in some cases this method can increase error by giving undue weight to one isolated station with anomalous temperature.
      Another source of difference is the method of averaging over the world, given the fact that data is not available everywhere. In the GISS method, we divide the Earth in four latitude belts. Within each belt the region with data is weighted by area. The anomaly for the entire belt is then taken as the anomaly for the portion of the belt that has data. The global anomaly is then the area-weighted mean of the four belts. This method gives equal weight to the hemispheres, but if one of the belts has little data that is not actually representative of the entire belt, substantial error can occur.
      The land (meteorological stations) data sets have substantial commonality, but they are not identical. Our approach, described in more detail in references 1, 4 and 7, uses GHCN (Global Historical Climatology Network) data, adjusting urban station data so that the long-term trend of the urban station matches that of neighboring rural stations, with the distinction between urban and rural based on either population or nightlights observed by satellite.
      Our ocean data is the "OI" analysis of Reynolds and Smith (2) for the period of satellite data, i.e., after 1982. Earlier ocean data is from Rayner et al. (3). These two ocean data sets are combined by working with anomalies for both data sets and defining anomalies relative to a common period, specifically 1982-1992.

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Further Information

Related webpages on the GISS website include: