Originally published by our Content Partner: Intergovernmental Panel on Climate Change (other articles)

Observations: Surface and Atmospheric Climate Change

This chapter should be cited as:
Trenberth, K.E., P.D. Jones, P. Ambenje, R. Bojariu, D. Easterling, A. Klein Tank, D. Parker, F. Rahimzadeh, J.A. Renwick, M. Rusticucci, B. Soden and P. Zhai, 2007: Observations: Surface and Atmospheric Climate Change. 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., D. Qin, M. Manning, Z. Chen, M. Marquis, K.B. Averyt, M. Tignor and H.L. Miller (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.

Executive Summary

Global mean surface temperatures have risen by 0.74°C ± 0.18°C when estimated by a linear trend over the last 100 years (1906–2005). The rate of warming over the last 50 years is almost double that over the last 100 years (0.13°C ± 0.03°C vs. 0.07°C ± 0.02°C per decade). Global mean temperatures averaged over land and ocean surfaces, from three different estimates, each of which has been independently adjusted for various homogeneity issues, are consistent within uncertainty estimates over the period 1901 to 2005 and show similar rates of increase in recent decades. The trend is not linear, and the warming from the first 50 years of instrumental record (1850–1899) to the last 5 years (2001–2005) is 0.76°C ± 0.19°C.

2005 was one of the two warmest years on record. The warmest years in the instrumental record of global surface temperatures are 1998 and 2005, with 1998 ranking first in one estimate, but with 2005 slightly higher in the other two estimates. 2002 to 2004 are the 3rd, 4th and 5th warmest years in the series since 1850. Eleven of the last 12 years (1995 to 2006) – the exception being 1996 – rank among the 12 warmest years on record since 1850. Surface temperatures in 1998 were enhanced by the major 1997–1998 El Niño but no such strong anomaly was present in 2005. Temperatures in 2006 were similar to the average of the past 5 years.

Land regions have warmed at a faster rate than the oceans. Warming has occurred in both land and ocean domains, and in both sea surface temperature (SST) and nighttime marine air temperature over the oceans. However, for the globe as a whole, surface air temperatures over land have risen at about double the ocean rate after 1979 (more than 0.27°C per decade vs. 0.13°C per decade), with the greatest warming during winter (December to February) and spring (March to May) in the Northern Hemisphere.

Changes in extremes of temperature are also consistent with warming of the climate. A widespread reduction in the number of frost days in mid-latitude regions, an increase in the number of warm extremes and a reduction in the number of daily cold extremes are observed in 70 to 75% of the land regions where data are available. The most marked changes are for cold (lowest 10%, based on 1961–1990) nights, which have become rarer over the 1951 to 2003 period. Warm (highest 10%) nights have become more frequent. Diurnal temperature range (DTR) decreased by 0.07°C per decade averaged over 1950 to 2004, but had little change from 1979 to 2004, as both maximum and minimum temperatures rose at similar rates. The record-breaking heat wave over western and central Europe in the summer of 2003 is an example of an exceptional recent extreme. That summer (June to August) was the hottest since comparable instrumental records began around 1780 (1.4°C above the previous warmest in 1807) and is very likely to have been the hottest since at least 1500.

Recent warming is strongly evident at all latitudes in SSTs over each of the oceans. There are inter-hemispheric differences in warming in the Atlantic, the Pacific is punctuated by El Niño events and Pacific decadal variability that is more symmetric about the equator, while the Indian Ocean exhibits steadier warming. These characteristics lead to important differences in regional rates of surface ocean warming that affect the atmospheric circulation.

Urban heat island effects are real but local, and have not biased the large-scale trends. A number of recent studies indicate that effects of urbanisation and land use change on the land-based temperature record are negligible (0.006ºC per decade) as far as hemispheric- and continental-scale averages are concerned because the very real but local effects are avoided or accounted for in the data sets used. In any case, they are not present in the SST component of the record. Increasing evidence suggests that urban heat island effects extend to changes in precipitation, clouds and DTR, with these detectable as a ‘weekend effect’ owing to lower pollution and other effects during weekends.

Average arctic temperatures increased at almost twice the global average rate in the past 100 years. Arctic temperatures have high decadal variability. A slightly longer warm period, almost as warm as the present, was also observed from the late 1920s to the early 1950s, but appears to have had a different spatial distribution than the recent warming.

Lower-tropospheric temperatures have slightly greater warming rates than those at the surface over the period 1958 to 2005. The radiosonde record is markedly less spatially complete than the surface record and increasing evidence suggests that it is very likely that a number of records have a cooling bias, especially in the tropics. While there remain disparities among different tropospheric temperature trends estimated from satellite Microwave Sounding Unit (MSU and advanced MSU) measurements since 1979, and all likely still contain residual errors, estimates have been substantially improved (and data set differences reduced) through adjustments for issues of changing satellites, orbit decay and drift in local crossing time (i.e., diurnal cycle effects). It appears that the satellite tropospheric temperature record is broadly consistent with surface temperature trends provided that the stratospheric influence on MSU channel 2 is accounted for. The range (due to different data sets) of global surface warming since 1979 is 0.16°C to 0.18°C per decade compared to 0.12°C to 0.19°C per decade for MSU estimates of tropospheric temperatures. It is likely, however, that there is slightly greater warming in the troposphere than at the surface, and a higher tropopause, with the latter due also to pronounced cooling in the stratosphere.

Lower stratospheric temperatures feature cooling since 1979. Estimates from adjusted radiosondes, satellites (MSU channel 4) and reanalyses are in qualitative agreement, suggesting a lower-stratospheric cooling of between 0.3°C and 0.6°C per decade since 1979. Longer radiosonde records (back to 1958) also indicate cooling but the rate of cooling has been significantly greater since 1979 than between 1958 and 1978. It is likely that radiosonde records overestimate stratospheric cooling, owing to changes in sondes not yet accounted for. Because of the stratospheric warming episodes following major volcanic eruptions, the trends are far from being linear.

Precipitation has generally increased over land north of 30°N over the period 1900 to 2005 but downward trends dominate the tropics since the 1970s. From 10°N to 30°N, precipitation increased markedly from 1900 to the 1950s, but declined after about 1970. Downward trends are present in the deep tropics from 10°N to 10°S, especially after 1976/1977. Tropical values dominate the global mean. It has become significantly wetter in eastern parts of North and South America, northern Europe, and northern and central Asia, but drier in the Sahel, the Mediterranean, southern Africa and parts of southern Asia. Patterns of precipitation change are more spatially and seasonally variable than temperature change, but where significant precipitation changes do occur they are consistent with measured changes in streamflow.

Substantial increases are found in heavy precipitation events. It is likely that there have been increases in the number of heavy precipitation events (e.g., 95th percentile) within many land regions, even in those where there has been a reduction in total precipitation amount, consistent with a warming climate and observed significant increasing amounts of water vapour in the atmosphere. Increases have also been reported for rarer precipitation events (1 in 50 year return period), but only a few regions have sufficient data to assess such trends reliably.

Droughts have become more common, especially in the tropics and subtropics, since the 1970s. Observed marked increases in drought in the past three decades arise from more intense and longer droughts over wider areas, as a critical threshold for delineating drought is exceeded over increasingly widespread areas. Decreased land precipitation and increased temperatures that enhance evapotranspiration and drying are important factors that have contributed to more regions experiencing droughts, as measured by the Palmer Drought Severity Index. The regions where droughts have occurred seem to be determined largely by changes in SSTs, especially in the tropics, through associated changes in the atmospheric circulation and precipitation. In the western USA, diminishing snow pack and subsequent reductions in soil moisture also appear to be factors. In Australia and Europe, direct links to global warming have been inferred through the extreme nature of high temperatures and heat waves accompanying recent droughts.

Tropospheric water vapour is increasing. Surface specific humidity has generally increased after 1976 in close association with higher temperatures over both land and ocean. Total column water vapour has increased over the global oceans by 1.2 ± 0.3% per decade from 1988 to 2004, consistent in pattern and amount with changes in SST and a fairly constant relative humidity. Strong correlations with SST suggest that total column water vapour has increased by 4% since 1970. Similar upward trends in upper-tropospheric specific humidity, which considerably enhance the greenhouse effect, have also been detected from 1982 to 2004.

‘Global dimming’ is neither global in extent nor has it continued after 1990. Reported decreases in solar radiation at the Earth’s surface from 1970 to 1990 have an urban bias and have reversed in sign. Although records are sparse, pan evaporation is estimated to have decreased in many places due to decreases in surface radiation associated with increases in clouds, changes in cloud properties and/or increases in air pollution (aerosols), especially from 1970 to 1990. However, in many of the same places, actual evapotranspiration inferred from surface water balance exhibits an increase in association with enhanced soil wetness from increased precipitation, as the actual evapotranspiration becomes closer to the potential evaporation measured by the pans. Hence, in determining evapotranspiration there is a trade-off between less solar radiation and increased surface wetness, with the latter generally dominant.

Cloud changes are dominated by the El Niño-Southern Oscillation and appear to be opposite over land and ocean. Widespread (but not ubiquitous) decreases in continental DTR since the 1950s coincide with increases in cloud amounts. Surface and satellite observations disagree about total and low-level cloud changes over the ocean. However, radiation changes at the top of the atmosphere from the 1980s to 1990s, possibly related in part to the El Niño-Southern Oscillation (ENSO) phenomenon, appear to be associated with reductions in tropical upper-level cloud cover, and are linked to changes in the energy budget at the surface and changes in observed ocean heat content.

Changes in the large-scale atmospheric circulation are apparent. Atmospheric circulation variability and change is largely described by relatively few major patterns. The dominant mode of global-scale variability on interannual time scales is ENSO, although there have been times when it is less apparent. The 1976–1977 climate shift, related to the phase change in the Pacific Decadal Oscillation (PDO) and more frequent El Niños, has affected many areas and most tropical monsoons. For instance, over North America, ENSO and Pacific-North American teleconnection-related changes appear to have led to contrasting changes across the continent, as the west has warmed more than the east, while the latter has become cloudier and wetter. There are substantial multi-decadal variations in the Pacific sector over the 20th century with extended periods of weakened (1900–1924; 1947–1976) as well as strengthened circulation (1925–1946; 1976–2005). Multi-decadal variability is also evident in the Atlantic as the Atlantic Multi-decadal Oscillation in both the atmosphere and the ocean.

Mid-latitude westerly winds have generally increased in both hemispheres. These changes in atmospheric circulation are predominantly observed as ‘annular modes’, related to the zonally averaged mid-latitude westerlies, which strengthened in most seasons from the 1960s to at least the mid-1990s, with poleward displacements of corresponding Atlantic and southern polar front jet streams and enhanced storm tracks. These were accompanied by a tendency towards stronger winter polar vortices throughout the troposphere and lower stratosphere. On monthly time scales, the southern and northern annular modes (SAM and NAM, respectively) and the North Atlantic Oscillation (NAO) are the dominant patterns of variability in the extratropics and the NAM and NAO are closely related. The westerlies in the Northern Hemisphere, which increased from the 1960s to the 1990s but which have since returned to about normal as part of NAO and NAM changes, alter the flow from oceans to continents and are a major cause of the observed changes in winter storm tracks and related patterns of precipitation and temperature anomalies, especially over Europe. In the Southern Hemisphere, SAM increases from the 1960s to the present are associated with strong warming over the Antarctic Peninsula and, to a lesser extent, cooling over parts of continental Antarctica. Analyses of wind and significant wave height support reanalysis-based evidence for an increase in extratropical storm activity in the Northern Hemisphere in recent decades until the late 1990s.

Intense tropical cyclone activity has increased since about 1970. Variations in tropical cyclones, hurricanes and typhoons are dominated by ENSO and decadal variability, which result in a redistribution of tropical storm numbers and their tracks, so that increases in one basin are often compensated by decreases over other oceans. Trends are apparent in SSTs and other critical variables that influence tropical thunderstorm and tropical storm development. Globally, estimates of the potential destructiveness of hurricanes show a significant upward trend since the mid-1970s, with a trend towards longer lifetimes and greater storm intensity, and such trends are strongly correlated with tropical SST. These relationships have been reinforced by findings of a large increase in numbers and proportion of hurricanes reaching categories 4 and 5 globally since 1970 even as total number of cyclones and cyclone days decreased slightly in most basins. The largest increase was in the North Pacific, Indian and southwest Pacific Oceans. However, numbers of hurricanes in the North Atlantic have also been above normal (based on 1981–2000 averages) in 9 of the last 11 years, culminating in the record-breaking 2005 season. Moreover, the first recorded tropical cyclone in the South Atlantic occurred in March 2004 off the coast of Brazil.

The temperature increases are consistent with observed changes in the cryosphere and oceans. Consistent with observed changes in surface temperature, there has been an almost worldwide reduction in glacier and small ice cap (not including Antarctica and Greenland) mass and extent in the 20th century; snow cover has decreased in many regions of the Northern Hemisphere; sea ice extents have decreased in the Arctic, particularly in spring and summer (Chapter 4); the oceans are warming; and sea level is rising (Chapter 5).

3.1 Introduction

This chapter assesses the observed changes in surface and atmospheric climate, placing new observations and new analyses made during the past six years (since the Third Assessment Report – TAR) in the context of the previous instrumental record. In previous IPCC reports, palaeo-observations from proxy data for the pre-instrumental past and observations from the ocean and ice domains were included within the same chapter. This helped the overall assessment of the consistency among the various variables and their synthesis into a coherent picture of change. However, the amount of information became unwieldy and is now spread over Chapters 3 to 6. Nevertheless, a short synthesis and scrutiny of the consistency of all the observations is included here (see Section 3.9).

In the TAR, surface temperature trends were examined from 1860 to 2000 globally, for 1901 to 2000 as maps and for three sub-periods (1910–1945, 1946–1975 and 1976–2000). The first and third sub-periods had rising temperatures, while the second sub-period had relatively stable global mean temperatures. The 1976 divide is the date of a widely acknowledged ‘climate shift’ (e.g., Trenberth, 1990) and seems to mark a time (see Chapter 9 of the full report) when global mean temperatures began a discernible upward trend that has been at least partly attributed to increases in greenhouse gas concentrations in the atmosphere (see the TAR; IPCC, 2001). The picture prior to 1976 has essentially not changed and is therefore not repeated in detail here. However, it is more convenient to document the sub-period after 1979, rather than 1976, owing to the availability of increased and improved satellite data since then (in particular Television InfraRed Observation Satellite (TIROS) Operational Vertical Sounder (TOVS) data) in association with the Global Weather Experiment (GWE) of 1979. The post-1979 period allows, for the first time, a global perspective on many fields of variables, such as precipitation, that was not previously available. For instance, the reanalyses of the global atmosphere from the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR, referred to as NRA; Kalnay et al., 1996; Kistler et al., 2001) and the European Centre for Medium Range Weather Forecasts (ECMWF, referred to as ERA-40; Uppala et al., 2005) are markedly more reliable after 1979, and spurious discontinuities are present in the analysed record at the end of 1978 (Santer et al., 1999; Bengtsson et al., 2004; Bromwich and Fogt, 2004; Simmons et al., 2004; Trenberth et al., 2005a). Therefore, the availability of high quality data has led to a focus on the post-1978 period, although physically this new regime seems to have begun in 1976/1977.

Documentation of the climate has traditionally analysed global and hemispheric means, and land and ocean means, and has presented some maps of trends. However, climate varies over all spatial and temporal scales: from the diurnal cycle to El Niño to multi-decadal and millennial variations. Atmospheric waves naturally create regions of temperature and moisture of opposite-signed departures from the zonal mean, as moist warm conditions are favoured in poleward flow while cool dry conditions occur in equator-ward flow. Although there is an infinite variety of weather systems, one area of recent substantial progress is recognition that a few preferred patterns (or modes) of variability determine the main seasonal and longer-term climate anomalies (Section 3.6). These patterns arise from the differential effects on the atmosphere of land and ocean, mountains, and anomalous heating, such as occurs during El Niño events. The response is generally felt in regions far removed from the anomalous forcing through atmospheric teleconnections, associated with large-scale waves in the atmosphere. This chapter therefore documents some aspects of temperature and precipitation anomalies associated with these preferred patterns, as they are vitally important for understanding regional climate anomalies (such as observed cooling in parts of the northern North Atlantic from 1901 to 2005; see Section 3.2.2.7, Figure 3.9) and why they differ from global means. Changes in storm tracks, the jet streams, regions of preferred blocking anticyclones and changes in monsoons all occur in conjunction with these preferred patterns and other climate anomalies. Therefore the chapter not only documents changes in variables, but also changes in phenomena (such as El Niño) or patterns, in order to increase understanding of the character of change.

Extremes of climate, such as droughts and wet spells, are very important because of their large impacts on society and the environment, but they are an expression of the variability. Therefore, the nature of variability at different spatial and temporal scales is vital to our understanding of extremes. The global means of temperature and precipitation are most readily linked to global mean radiative forcing and are important because they clearly indicate if unusual change is occurring. However, the local or regional response can be complex and perhaps even counter-intuitive, such as changes in planetary waves in the atmosphere induced by global warming that result in regional cooling. As an indication of the complexity associated with temporal and spatial scales, Table 3.1.

provides measures of the magnitude of natural variability of surface temperature in which climate signals are embedded. The measures used are indicators of the range: the mean range of the diurnal and annual cycles, and the estimated 5th to 95th percentiles range of anomalies. These are based on the standard deviation and assumed normal distribution, which is a reasonable approximation in many places for temperature, with the exception of continental interiors in the cold season, which have strongly negatively skewed temperature distributions owing to cold extremes. For the global mean, the variance is somewhat affected by the observed trend, which inflates this estimate of the range slightly. The comparison highlights the large diurnal cycle and daily variability. Daily variability is, however, greatly reduced by either spatial or temporal averaging that effectively averages over synoptic weather systems. Nevertheless, even continental scale averages contain much greater variability than the global mean in association with planetary-scale waves and events such as El Niño.

Throughout the chapter, the authors try to consistently indicate the degree of confidence and uncertainty in trends and other results, as given by Box TS.1 in the Technical Summary (TS). Quantitative estimates of uncertainty include: for the mean, the 5th and 95th percentiles; and for trends, statistical significance at the 0.05 (5%) significance level. This allows assessment of what is unusual. The chapter mainly uses the word ‘trend’ to designate a generally monotonic change in the level of a variable. Where numerical values are given, they are equivalent linear trends, though more complex changes in the variable will often be clear from the description. The chapter also assesses, if possible, the physical consistency among different variables, which helps to provide additional confidence in trends.

Frequently Asked Question 3.1 How are Temperatures on Earth Changing?

FAQ 3.1, Figure 6: (Top) Annual global mean observed temperatures1 (black dots) along with simple fits to the data. The left hand axis shows anomalies relative to the 1961 to 1990 average and the right hand axis shows the estimated actual temperature (°C). Linear trend fits to the last 25 (yellow), 50 (orange), 100 (purple) and 150 years (red) are shown, and correspond to 1981 to 2005, 1956 to 2005, 1906 to 2005, and 1856 to 2005, respectively. Note that for shorter recent periods, the slope is greater, indicating accelerated warming. The blue curve is a smoothed depiction to capture the decadal variations. To give an idea of whether the fluctuations are meaningful, decadal 5% to 95% (light blue) error ranges about that line are given (accordingly, annual values do exceed those limits). Results from climate models driven by estimated radiative forcings for the 20th century (Chapter 9) suggest that there was little change prior to about 1915, and that a substantial fraction of the early 20th-century change was contributed by naturally occurring influences including solar radiation changes, volcanism and natural variability. From about 1940 to 1970 the increasing industrialisation following World War II increased pollution in the Northern Hemisphere, contributing to cooling, and increases in carbon dioxide and other greenhouse gases dominate the observed warming after the mid-1970s. (Bottom) Patterns of linear global temperature trends from 1979 to 2005 estimated at the surface (left), and for the troposphere (right) from the surface to about 10 km altitude, from satellite records. Grey areas indicate incomplete data. Note the more spatially uniform warming in the satellite tropospheric record while the surface temperature changes more clearly relate to land and ocean. (Source: IPCC 2007) Instrumental observations over the past 157 years show that temperatures at the surface have risen globally, with important regional variations. For the global average, warming in the last century has occurred in two phases, from the 1910s to the 1940s (0.35°C), and more strongly from the 1970s to the present (0.55°C). An increasing rate of warming has taken place over the last 25 years, and 11 of the 12 warmest years on record have occurred in the past 12 years. Above the surface, global observations since the late 1950s show that the troposphere (up to about 10 km) has warmed at a slightly greater rate than the surface, while the stratosphere (about 10–30 km) has cooled markedly since 1979. This is in accord with physical expectations and most model results. Confirmation of global warming comes from warming of the oceans, rising sea levels, glaciers melting, sea ice retreating in the Arctic and diminished snow cover in the Northern Hemisphere. There is no single thermometer measuring the global temperature. Instead, individual thermometer measurements taken every day at several thousand stations over the land areas of the world are combined with thousands more measurements of sea surface temperature taken from ships moving over the oceans to produce an estimate of global average temperature every month. To obtain consistent changes over time, the main analysis is actually of anomalies (departures from the climatological mean at each site) as these are more robust to changes in data availability. It is now possible to use these measurements from 1850 to the present, although coverage is much less than global in the second half of the 19th century, is much better after 1957 when measurements began in Antarctica, and best after about 1980, when satellite measurements began. Expressed as a global average, surface temperatures have increased by about 0.74°C over the past hundred years (between 1906 and 2005; see Figure 6). However, the warming has been neither steady nor the same in different seasons or in different locations. There was not much overall change from 1850 to about 1915, aside from ups and downs associated with natural variability but which may have also partly arisen from poor sampling. An increase (0.35°C) occurred in the global average temperature from the 1910s to the 1940s, followed by a slight cooling (0.1°C), and then a rapid warming (0.55°C) up to the end of 2006 (Figure 6). The warmest years of the series are 1998 and 2005 (which are statistically indistinguishable), and 11 of the 12 warmest years have occurred in the last 12 years (1995 to 2006). Warming, particularly since the 1970s, has generally been greater over land than over the oceans. Seasonally, warming has been slightly greater in the winter hemisphere. Additional warming occurs in cities and urban areas (often referred to as the urban heat island effect), but is confined in spatial extent, and its effects are allowed for both by excluding as many of the affected sites as possible from the global temperature data and by increasing the error range (the blue band in the figure). A few areas have cooled since 1901, most notably the northern North Atlantic near southern Greenland. Warming during this time has been strongest over the continental interiors of Asia and northern North America. However, as these are areas with large year-to-year variability, the most evident warming signal has occurred in parts of the middle and lower latitudes, particularly the tropical oceans. In the lower left panel of Figure 6, which shows temperature trends since 1979, the pattern in the Pacific Ocean features warming and cooling regions related to El Niño. Analysis of long-term changes in daily temperature extremes has recently become possible for many regions of the world (parts of North America and southern South America, Europe, northern and eastern Asia, southern Africa and Australasia). Especially since the 1950s, these records show a decrease in the number of very cold days and nights and an increase in the number of extremely hot days and warm nights (see FAQ 3.3). The length of the frost-free season has increased in most mid- and high-latitude regions of both hemispheres. In the Northern Hemisphere, this is mostly manifest as an earlier start to spring. In addition to the surface data described above, measurements of temperature above the surface have been made with weather balloons, with reasonable coverage over land since 1958, and from satellite data since 1979. All data are adjusted for changes in instruments and observing practices where necessary. Microwave satellite data have been used to create a ‘satellite temperature record’ for thick layers of the atmosphere including the troposphere (from the surface up to about 10 km) and the lower stratosphere (about 10 to 30 km). Despite several new analyses with improved cross-calibration of the 13 instruments on different satellites used since 1979 and compensation for changes in observing time and satellite altitude, some uncertainties remain in trends. For global observations since the late 1950s, the most recent versions of all available data sets show that the troposphere has warmed at a slightly greater rate than the surface, while the stratosphere has cooled markedly since 1979. This is in accord with physical expectations and most model results, which demonstrate the role of increasing greenhouse gases in tropospheric warming and stratospheric cooling; ozone depletion also contributes substantially to stratospheric cooling. Consistent with observed increases in surface temperature, there have been decreases in the length of river and lake ice seasons. Further, there has been an almost worldwide reduction in glacial mass and extent in the 20th century; melting of the Greenland Ice Sheet has recently become apparent; snow cover has decreased in many Northern Hemisphere regions; sea ice thickness and extent have decreased in the Arctic in all seasons, most dramatically in spring and summer; the oceans are warming; and sea level is rising due to thermal expansion of the oceans and melting of land ice.

3.2 Changes in Surface Climate: Temperature

3.2.1 Background

Improvements have been made to both land surface air temperature and sea surface temperature (SST) databases during the six years since the TAR was published. Jones and Moberg (2003) revised and updated the Climatic Research Unit (CRU) monthly land-surface air temperature record, improving coverage particularly in the Southern Hemisphere (SH) in the late 19th century. Further revisions by Brohan et al. (2006) include a comprehensive reassessment of errors together with an extension back to 1850. Under the auspices of the World Meteorological Organization (WMO) and the Global Climate Observing System (GCOS), daily temperature (together with precipitation and pressure) data for an increasing number of land stations have also become available, allowing more detailed assessment of extremes (see Section 3.8), as well as potential urban influences on both large-scale temperature averages and microclimate. A new gridded data set of monthly maximum and minimum temperatures has updated earlier work (Vose et al., 2005a). For the oceans, the International Comprehensive Ocean-Atmosphere Data Set (ICOADS) has been extended by blending the former COADS with the UK’s Marine Data Bank and newly digitised data, including the US Maury Collection and Japan’s Kobe Collection. As a result, coverage has been improved substantially before 1920, especially over the Pacific, with further modest improvements up to 1950 (Worley et al., 2005; Rayner et al., 2006). Improvements have also been made in the bias reduction of satellite-based infrared (Reynolds et al., 2002) and microwave (Reynolds et al., 2004; Chelton and Wentz, 2005) retrievals of SST for the 1980s onwards. These data represent ocean skin temperature (Section 3.2.2.3), not air temperature or SST, and so must be adjusted to match the latter. Satellite infrared and microwave imagery can now also be used to monitor land surface temperature (Peterson et al., 2000; Jin and Dickinson, 2002; Kwok and Comiso, 2002b). Microwave imagery must allow for variations in surface emissivity and cannot act as a surrogate for air temperature over either snow covered (Peterson et al., 2000) or sea-ice areas. As satellite based records are still short in duration, all regional and hemispheric temperature series shown in this section are based on conventional surface-based data sets, except where stated.

Despite these improvements, substantial gaps in data coverage remain, especially in the tropics and the SH, particularly Antarctica. These gaps are largest in the 19th century and during the two world wars. Accordingly, advanced interpolation and averaging techniques have been applied when creating global data sets and hemispheric and global averages (Smith and Reynolds, 2005), and advanced techniques have also been used in the estimation of errors (Brohan et al., 2006), both locally and on a global basis (see Appendix B.1). These errors, as well as the influence of decadal and multi-decadal variability in the climate, have been taken into account when estimating linear trends and their uncertainties (see Appendix A). Estimates of surface temperature from ERA-40 reanalyses have been shown to be of climate quality (i.e., without major time-varying biases) at large scales from 1979 (Simmons et al., 2004). Improvements in ERA-40 over NRA arose from both improved data sources and better assimilation techniques (Uppala et al., 2005). The performance of ERA-40 was degraded prior to the availability of satellite data in the mid-1970s (see Appendix B.5).

3.2.2 Temperature in the Instrumental Record for Land and Oceans

3.2.2.1 Land-Surface Air Temperature

Figure 3.1 shows annual global land-surface air temperatures, relative to the period 1961 to 1990, from the improved analysis (CRU/Hadley Centre gridded land-surface air temperature version 3; CRUTEM3) of Brohan et al. (2006). The longterm variations are in general agreement with those from the operational version of the Global Historical Climatology Network (GHCN) data set (National Climatic Data Center (NCDC); Smith and Reynolds, 2005; Smith et al. 2005), and with the National Aeronautics and Space Administration’s (NASA) Goddard Institute for Space Studies (GISS; Hansen et al., 2001) and Lugina et al. (2005) analyses (Figure 3.1). Most of the differences arise from the diversity of spatial averaging techniques. The global average for CRUTEM3 is a land-area weighted sum (0.68 × NH + 0.32 × SH). For NCDC it is an area-weighted average of the grid-box anomalies where available worldwide. For GISS it is the average of the anomalies for the zones 90°N to 23.6°N, 23.6°N to 23.6°S and 23.6°S to 90°S with weightings 0.3, 0.4 and 0.3, respectively, proportional to their total areas. For Lugina et al. (2005) it is (NH + 0.866 × SH) / 1.866 because they excluded latitudes south of 60°S. As a result, the recent global trends are largest in CRUTEM3 and NCDC, which give more weight to the NH where recent trends have been greatest (Table 3.2).

Further, small differences arise from the treatment of gaps in the data. The GISS gridding method favours isolated island and coastal sites, thereby reducing recent trends, and Lugina et al. (2005) also obtain reduced recent trends owing to their optimal interpolation method that tends to adjust anomalies towards zero where there are few observations nearby (see, e.g., Hurrell and Trenberth, 1999). The NCDC analysis, which begins in 1880, is higher than CRUTEM3 by between 0.1°C and 0.2°C in the first half of the 20th century and since the late 1990s. This is probably because its anomalies have been interpolated to be spatially complete: an earlier but very similar version (CRUTEM2v; Jones and Moberg, 2003) agreed very closely with NCDC when the global averages were calculated in the same way (Vose et al., 2005b). Differences may also arise because the numbers of stations used by CRUTEM3, NCDC and GISS differ (4,349, 7,230 and >7,200 respectively), although many of the basic station data are in common. Differences in station numbers relate principally to CRUTEM3 requiring series to have sufficient data between 1961 and 1990 to allow the calculation of anomalies (Brohan et al., 2006). Further differences may have arisen from differing homogeneity adjustments (see also Appendix B.2).

Trends and low-frequency variability of large-scale surface air temperature from the ERA-40 reanalysis and from CRUTEM2v (Jones and Moberg, 2003) are in general agreement from the late 1970s onwards (Simmons et al., 2004). When ERA-40 is sub-sampled to match the Jones and Moberg coverage, correlations between monthly hemispheric- and continental-scale averages exceed 0.96, although trends in ERA-40 are then 0.03°C and 0.07°C per decade (NH and SH, respectively) lower than Jones and Moberg (2003). The ERA-40 reanalysis is more homogeneous than previous reanalyses (see Section 3.2.1 and Appendix B.5.4) but is not completely independent of the Jones and Moberg data (Simmons et al., 2004). The warming trends continue to be greatest over the continents of the NH (see maps in Section 3.2.2.7, Figures 3.9 and 3.10), in line with the TAR. Issues of homogeneity of terrestrial air temperatures are discussed in Appendix B.2.

Figure 3.1. Annual anomalies of global land-surface air temperature (°C), 1850 to 2005, relative to the 1961 to 1990 mean for CRUTEM3 updated from Brohan et al. (2006). The smooth curves show decadal variations (see Appendix A). The black curve from CRUTEM3 is compared with those from NCDC (Smithand Reynolds, 2005; blue), GISS (Hansen et al., 2001; red) and Lugina et al. (2005; green).

Table 3.2 provides trend estimates from a number of hemispheric and global temperature databases. Warming since 1979 in CRUTEM3 has been 0.27°C per decade for the globe, but 0.33°C and 0.13°C per decade for the NH and SH, respectively. Brohan et al. (2006) and Rayner et al. (2006) (see Section 3.2.2.3) provide uncertainties for annual estimates, incorporating the effects of measurement and sampling error, and uncertainties regarding biases due to urbanisation and earlier methods of measuring SST. These factors are taken into account, although ignoring their serial correlation. In Table 3.2, the effects of persistence on error bars are accommodated using a red noise approximation, which effectively captures the main influences. For more extensive discussion see Appendix A.

From 1950 to 2004, the annual trends in minimum and maximum land-surface air temperature averaged over regions with data were 0.20°C per decade and 0.14°C per decade, respectively, with a trend in diurnal temperature range (DTR) of –0.07°C per decade (Vose et al., 2005a; Figure 3.2). This is consistent with the TAR where data extended from 1950 to 1993; spatial coverage is now 71% of the terrestrial surface instead of 54% in the TAR, although tropical areas are still under-represented. Prior to 1950, insufficient data are available to develop global-scale maps of maximum and minimum temperature trends. For 1979 to 2004, the corresponding linear trends for the land areas where data are available were 0.29°C per decade for both maximum and minimum temperature with no trend for DTR. Diurnal temperature range is particularly sensitive to observing techniques, and monitoring it requires adherence to GCOS monitoring principles (GCOS, 2004). A map of the trend of annual DTR over the period 1979 to 2004 (see Section 3.2.2.7, Figure 3.11) is discussed later in the chapter.

3.2.2.2 Urban Heat Islands and Land Use Effects

The modified land surface in cities affects the storage and radiative and turbulent transfers of heat and its partition into sensible and latent components (see Section 7.2 and Box 7.2). The relative warmth of a city compared with surrounding rural areas, known as the urban heat island (UHI) effect, arises from these changes and may also be affected by changes in water runoff, pollution and aerosols. Urban heat island effects are often very localised and depend on local climate factors such as windiness and cloudiness (which in turn depend on season), and on proximity to the sea. Section 3.3.2.4 discusses impacts of urbanisation on precipitation.

Figure 3.2. Annual anomalies of maximum and minimum temperatures and DTR (°C) relative to the 1961 to 1990 mean, averaged for the 71% of global land areas where data are available for 1950 to 2004. The smooth curves show decadal variations (see Appendix A). Adapted from Vose et al. (2005a).

Many local studies have demonstrated that the microclimate within cities is on average warmer, with a smaller DTR, than if the city were not there. However, the key issue from a climate change standpoint is whether urban-affected temperature records have significantly biased large-scale temporal trends. Studies that have looked at hemispheric and global scales conclude that any urban-related trend is an order of magnitude smaller than decadal and longer time-scale trends evident in the series (e.g., Jones et al., 1990; Peterson et al., 1999). This result could partly be attributed to the omission from the gridded data set of a small number of sites (<1%) with clear urban-related warming trends. In a worldwide set of about 270 stations, Parker (2004, 2006) noted that warming trends in night minimum temperatures over the period 1950 to 2000 were not enhanced on calm nights, which would be the time most likely to be affected by urban warming. Thus, the global land warming trend discussed is very unlikely to be influenced significantly by increasing urbanisation (Parker, 2006). Over the conterminous USA, after adjustment for time-of-observation bias and other changes, rural station trends were almost indistinguishable from series including urban sites (Peterson, 2003; Figure 3.3), and similar considerations apply to China from 1951 to 2001 (Li et al., 2004). One possible reason for the patchiness of UHIs is the location of observing stations in parks where urban influences are reduced (Peterson, 2003). In summary, although some individual sites may be affected, including some small rural locations, the UHI effect is not pervasive, as all global-scale studies indicate it is a very small component of large-scale averages. Accordingly, this assessment adds the same level of urban warming uncertainty as in the TAR: 0.006°C per decade since 1900 for land, and 0.002°C per decade since 1900 for blended land with ocean, as ocean UHI is zero. These uncertainties are added to the cool side of the estimated temperatures and trends, as explained by Brohan et al. (2006), so that the error bars in Section 3.2.2.4, Figures 3.6 and 3.7 and FAQ 3.1 are slightly asymmetric. The statistical significances of the trends in Table 3.2 and Section 3.2.2.4, Table 3.3 take account of this asymmetry.

McKitrick and Michaels (2004) and De Laat and Maurellis (2006) attempted to demonstrate that geographical patterns of warming trends over land are strongly correlated with geographical patterns of industrial and socioeconomic development, implying that urbanisation and related land surface changes have caused much of the observed warming. However, the locations of greatest socioeconomic development are also those that have been most warmed by atmospheric circulation changes (Sections 3.2.2.7 and 3.6.4), which exhibit large-scale coherence. Hence, the correlation of warming with industrial and socioeconomic development ceases to be statistically significant. In addition, observed warming has been, and transient greenhouse-induced warming is expected to be, greater over land than over the oceans (Chapter 10), owing to the smaller thermal capacity of the land.

Figure 3.3. Anomaly (°C) time series relative to the 1961 to 1990 mean of the full US Historical Climatology Network (USHCN) data (red), the USHCN data without the 16% of the stations with populations of over 30,000 within 6 km in the year 2000 (blue), and the 16% of the stations with populations over 30,000 (green). The full USHCN set minus the set without the urban stations is shown in magenta. Both the full data set and the data set without the high-population stations had stations in all of the 2.5° latitude by 3.5° longitude grid boxes during the entire period plotted, but the subset of high-population stations only had data in 56% of these grid boxes. Adapted from Peterson and Owen (2005).

Comparing surface temperature estimates from the NRA with raw station time series, Kalnay and Cai (2003) concluded that more than half of the observed decrease in DTR in the eastern USA since 1950 was due to changes in land use, including urbanisation. This conclusion was based on the fact that the reanalysis did not explicitly include these factors, which would affect the observations. However, the reanalysis also did not explicitly include many other natural and anthropogenic effects, such as increasing greenhouse gases and observed changes in clouds or soil moisture (Trenberth, 2004). Vose et al. (2004) showed that the adjusted station data for the region (for homogeneity issues, see Appendix B.2) do not support Kalnay and Cai’s conclusions. Nor are Kalnay and Cai’s results reproduced in the ERA-40 reanalysis (Simmons et al., 2004). Instead, most of the changes appear related to abrupt changes in the type of data assimilated into the reanalysis, rather than to gradual changes arising from land use and urbanisation changes. Current reanalyses may be reliable for estimating trends since 1979 (Simmons et al., 2004) but are in general unsuited for estimating longer-term global trends, as discussed in Appendix B.5.

Nevertheless, changes in land use can be important for DTR at the local-to-regional scale. For instance, land degradation in northern Mexico resulted in an increase in DTR relative to locations across the border in the USA (Balling et al., 1998), and agriculture affects temperatures in the USA (Bonan, 2001; Christy et al., 2006). Desiccation of the Aral Sea since 1960 raised DTR locally (Smallet al., 2001). By processing maximum and minimum temperature data as a function of day of the week, Forster and Solomon (2003) found a distinctive ‘weekend effect’ in DTR at stations examined in the USA, Japan, Mexico and China. The weekly cycle in DTR has a distinctive large-scale pattern with geographically varying sign, and strongly suggests an anthropogenic effect on climate, likely through changes in pollution and aerosols (Jin et al., 2005). Section 7.2 provides fuller discussion of the effects of land use changes.

3.2.2.3 Sea Surface temperature and Marine Air temperature

Most analyses of SST estimate the subsurface bulk temperature (i.e., the temperature in the uppermost few metres of the ocean), not the ocean skin temperature measured by satellites. For maximum resolution and data coverage, polar orbiting infrared satellite data since 1981 can be used so long as the satellite ocean skin temperatures are adjusted to estimate bulk SST values through a calibration procedure (see e.g., Reynolds et al., 2002; Rayner et al., 2003, 2006; Appendix B.3). But satellite SST data alone have not been used as a major resource for estimating climate change because of their strong time-varying biases which are hard to completely remove, for example, as shown in Reynolds et al. (2002) for the Pathfinder polar orbiting satellite SST data set (Kilpatrick et al., 2001). Figures 3.9 and 3.10 (Section 3.2.2.7) do, however, make use of spatial relationships based on adjusted satellite SST estimates after November 1981 to provide nearer-to-global coverage for the 1979 to 2005 period, and O’Carroll et al. (2006) have developed an analysis based on Along-Track Scanning Radiometers (ATSRs) with potential for the future. However, satellite data are unable to fill in estimates of surface temperature over or near sea ice areas.

Recent bulk SSTs estimated using ship and buoy data also have time-varying biases (e.g., Christy et al., 2001; Kent and Kaplan, 2006) that are larger than originally estimated by Folland et al. (1993), but not large enough to prejudice conclusions about recent warming (see Appendix B.3). As reported in the TAR, a combined physical-empirical method (Folland and Parker, 1995) is mainly used to estimate adjustments to ship SST data obtained up to 1941 to compensate for heat losses from uninsulated (mainly canvas) or partly insulated (mainly wooden) buckets. Details are given in Appendix B.3.

The SST analyses of Rayner et al. (2003) and Smith and Reynolds (2004) are interpolated to fill missing data areas. The main problem for estimating climate variations in the presence of large data gaps is underestimation of change, as most interpolation procedures tend to bias the analysis towards the modern climatologies used in these data sets (Hurrell and Trenberth, 1999). To address non-stationary aspects, Rayner et al. (2003) extracted the leading global covariance pattern, which represents long-term changes, before interpolating using reduced-space optimal interpolation (see Appendix B.1); and Smith and Reynolds removed a smoothed, moving 15-year average field before interpolating by a related technique.

Figure 3.4. (a) Annual anomalies of global SST (HadSST2; red bars and blue solid curve), 1850 to 2005, and global NMAT (HadMAT, green curve), 1856 to 2005, relative to the 1961 to 1990 mean (°C) from the UK Meteorological Office (UKMO; Rayner et al., 2006). The smooth curves show decadal variations (see Appendix 3.A). The dashed black curve shows equivalent smoothed SST anomalies from the TAR. (b) Smoothed annual global SST anomalies, relative to 1961 to 1990 (°C), from HadSST2 (blue line, as in (a)), from NCDC (Smith et al., 2005; red line) and from COBE-SST (Ishii et al., 2005; green line). The latter two series begin later in the 19th century than HadSST2. (c,d) As in (a) but for the NH and SH showing only the UKMO series

Figure 3.4a shows annual and decadally smoothed anomalies of global SST from the new, uninterpolated Hadley Centre SST data set version 2 (HadSST2) analysis (Rayner et al., 2006). Figure 3.4a also shows NMAT (referred to as HadMAT: Hadley Centre Marine Air temperature data set), which is used to avoid daytime heating of ship decks (Bottomley et al., 1990). The global averages are ocean-area weighted sums (0.44 × NH + 0.56 × SH). The HadMAT analysis includes limited optimal interpolation (Rayner et al., 2003) and was chosen because of the demonstration by Folland et al. (2003) of its skill in the sparsely observed South Pacific from the late 19th century onwards, but major gaps (e.g., the Southern Ocean) are not interpolated. Although HadMAT data have been corrected for warm biases during World War II they may still be too warm in the NH and too cool in the SH at that time (Figure 3.4c,d). However, global HadSST2 and HadMAT generally agree well, especially after the 1880s. The SST analysis in the TAR is included in Figure 3.4a. The changes in SST since the TAR are generally fairly small, though the new SST analysis is warmer around 1880 and cooler in the 1950s. The peak warmth in the early 1940s is likely to have arisen partly from closely spaced multiple El Niño events (Brönnimann et al., 2004; see also Section 3.6.2) and also due to the warm phase of the Atlantic Multi-decadal Oscillation (AMO; see Section 3.6.6). The HadMAT data generally confirm the hemispheric SST trends in the 20th century (Figure 3.4c,d and Table 3.2). Overall, the SST data should be regarded as more reliable because averaging of fewer samples is needed for SST than for HadMAT to remove synoptic weather noise. However, the changes in SST relative to NMAT since 1991 in the tropical Pacific may be partly real (Christy et al., 2001). As the atmospheric circulation changes, the relationship between SST and surface air temperature anomalies can change along with surface fluxes. Interannual variations in the heat fluxes to the atmosphere can exceed 100 W m^-2 locally in individual months, but the main prolonged variations occur with the El Niño-Southern Oscillation (ENSO), where changes in the central tropical Pacific exceed ±50 W m^-2 for many months during major ENSO events (Trenberth et al., 2002a).

Figure 3.4b shows three time series of changes in global SST. Neither the HadSST2 series (as in Figure 3.4a) nor the NCDC series include polar-orbiting satellite data because of possible time-varying biases that remain difficult to correct fully (Rayner et al., 2003). The Japanese series (Ishii et al., 2005; referred to as Centennial in-situ Observation-Based Estimates of SSTs (COBE-SST) from the Japan Meteorological Agency (JMA)) is also in situ except for the specification of sea ice. The warmest year globally in each SST record was 1998 (0.44°C, 0.38°C and 0.37°C above the 1961 to 1990 average for HadSST2, NCDC and COBE-SST, respectively). The five warmest years in all analyses have occurred after 1995.

Figure 3.5. Latitude-time sections of zonal mean temperature anomalies (°C) from 1900 to 2005, relative to the 1961 to 1990 mean. Left panels: SST annual anomalies across each ocean from HadSST2 (Rayner et al., 2006). Right panels: Surface temperature annual anomalies for land (top, CRUTEM3) and land plus ocean (bottom, HadCRUT3). Values are smoothed with the 5-point filter to remove fluctuations of less than about six years (see Appendix A); and white areas indicate missing data.

Understanding of the variability and trends in different oceans is still developing, but it is already apparent that they are quite different. The Pacific is dominated by ENSO and modulated by the Pacific Decadal Oscillation (PDO), which may provide ways of moving heat from the tropical ocean to higher latitudes and out of the ocean into the atmosphere (Trenberth et al., 2002a), thereby greatly altering how trends are manifested. In the Atlantic, observations reveal the role of the AMO (Folland et al., 1999; Delworth and Mann, 2000; Enfield et al., 2001; Goldenberg et al., 2001; Section 3.6.6 and Figure 3.33). The AMO is likely to be associated with the Thermohaline Circulation (THC), which transports heat northwards, thereby moderating the tropics and warming the high latitudes. In the Indian Ocean, interannual variability is small compared with the trend. Figure 3.5 presents latitude-time sections from 1900 for SSTs (from HadSST2) for the zonal mean across each ocean, filtered to remove fluctuations of less than about six years, including the ENSO signal. In the Pacific, the long-term warming is clearly evident, but punctuated by cooler episodes centred in the tropics, and no doubt linked to the PDO. The prolonged 1939–1942 El Niño shows up as a warm interval. In the Atlantic, the warming from the 1920s to about 1940 in the NH was focussed on higher latitudes, with the SH remaining cool. This inter-hemispheric contrast is believed to be one signature of the THC (Zhang and Delworth, 2005). The subsequent relative cooling in the NH extratropics and the more recent intense warming in NH mid-latitudes was predominantly a multi-decadal variation of SST; only in the last decade is an overall warming signal clearly emerging. Therefore, the recent strong warming appears to be related in part to the AMO in addition to a global warming signal (Section 3.6.6). The cooling in the northwestern North Atlantic just south of Greenland, reported in the SAR, has now been replaced by strong warming (see also Section 3.2.2.7, Figures 3.9 and 3.10; also Figures 5.1 and 5.2 for ocean heat content). The Indian Ocean also reveals a poorly observed warm interval in the early 1940s, and further shows the fairly steady warming in recent years. The multi-decadal variability in the Atlantic has a much longer time scale than that in the Pacific, but it is noteworthy that all oceans exhibit a warm period around the early 1940s.

3.2.2.4 Land and Sea Combined temperature: Global, Northern Hemisphere, Southern Hemisphere and Zonal Means

Gridded data sets combining land-surface air temperature and SST anomalies have been developed and maintained by three groups: CRU with the UKMO Hadley Centre in the UK (HadCRUT3; Brohan et al., 2006) and NCDC (Smith and Reynolds, 2005) and GISS (Hansen et al., 2001) in the USA. Although the component data sets differ slightly (see Sections 3.2.2.1 and 3.2.2.3) and the combination methods also differ, trends are similar. Table 3.3 provides comparative estimates of linear trends. Overall warming since 1901 has been a little less in the NCDC and GISS analysis than in the HadCRUT3 analysis. All series indicate that the warmest five years have occurred after 1997, although there is slight disagreement about the ordering. The HadCRUT3 data set shows 1998 as warmest, while 2005 is warmest in NCDC and GISS data. Thus the year 2005, with no El Niño, was about as warm globally as 1998 with its major El Niño effects. The GISS analysis of 2005 interpolated the exceptionally warm conditions in the extreme north of Eurasia and North America over the Arctic Ocean (see Figure 3.5). If the GISS data for 2005 are averaged only south of 75°N, then 2005 is cooler than 1998. In addition, there were relatively cool anomalies in 2005 in HadCRUT3 in parts of Antarctica and the Southern Ocean, where sea ice coverage (see Chapter 4) has not declined.

Hemispheric and global series based on Brohan et al. (2006) are shown in Figure 3.6 and tropical and polar series in Figure 3.7. Owing to the sparsity of SST data, the polar series are for land only. The recent warming is strongest in the NH extratropics, while El Niño events are clearly evident in the tropics, particularly the 1997–1998 event that makes 1998 the warmest year in HadCRUT3. The warming over land in the Arctic north of 65°N (Figure 3.7) is more than double the warming in the global mean from the 19th century to the 21st century and also from about the late 1960s to the present. In the arctic series, 2005 is the warmest year. A slightly longer warm period, almost as warm as the present, was observed from the late 1920s to the early 1950s. Although data coverage was limited in the first half of the 20th century, the spatial pattern of the earlier warm period appears to have been different from that of the current warmth. In particular, the current warmth is partly linked to the Northern Annular Mode (NAM; see Section 3.6.4) and affects a broader region (Polyakov et al., 2003). Temperatures over mainland Antarctica (south of 65°S) have not warmed in recent decades (Turner et al., 2005), but it is virtually certain that there has been strong warming over the last 50 years in the Antarctic Peninsula region (Turner et al., 2005; see the discussion of changes in the Southern Annular Mode (SAM) and Figure 3.32 in Section 3.6.5).

3.2.2.5 Consistency between Land and Ocean Surface Temperature Changes

Figure 3.6. Global and hemispheric annual combined land-surface air temperature and SST anomalies (°C) (red) for 1850 to 2006 relative to the 1961 to 1990 mean, along with 5 to 95% error bar ranges, from HadCRUT3 (adapted from Brohan et al., 2006). The smooth blue curves show decadal variations (see Appendix A).

Figure 3.7. Annual temperature anomalies (°C) up to 2005, relative to the 1961 to 1990 mean (red) with 5 to 95% error bars. The tropical series (middle) is combined land-surface air temperature and SST from HADCRUT3 (adapted from Brohan et al., 2006). The polar series (top and bottom) are land-only from CRUTEM3, because SST data are sparse and unreliable in sea ice zones. The smooth blue curves show decadal variations (see Appendix A).

The course of temperature change over the 20th century, revealed by the independent analysis of land air temperatures, SST and NMAT, is generally consistent (Figure 3.8). Warming occurred in two distinct phases (1915–1945 and since 1975), and it has been substantially stronger over land than over the oceans in the later phase, as shown also by the trends in Table 3.2. The land component has also been more variable from year to year (compare Figures 3.1 and 3.4a,c,d). Much of the recent difference between global SST (and NMAT) and global land air temperature trends has arisen from accentuated warming over the continents in the mid-latitude NH (Section 3.2.2.7, Figures 3.9 and 3.10). This is likely to be related to greater evaporation and heat storage in the ocean, and in particular to atmospheric circulation changes in the winter half-year due to the North Atlantic Oscillation (NAO)/NAM (see discussion in Section 3.6.4). Accordingly the differences between NH and SH temperatures follow a course similar to the plot of land air temperature minus SST shown in Figure 3.8.

3.2.2.6 Temporal Variability of Global Temperatures and Recent Warming

Figure 3.8. Annual anomalies (°C) of global average SST (blue curve, begins 1850), NMAT (green curve, begins 1856) and land-surface air temperature (red curve, begins 1850) to 2005, relative to their 1961 to 1990 means (Brohan et al., 2006; Rayner et al., 2006). The smooth curves show decadal variations (see Appendix A). Inset shows the smoothed differences between the land-surface air temperature and SST anomalies (i.e., red minus blue).

The standard deviation of the HadCRUT3 annual average temperatures for the globe for 1850 to 2005 shown in Figure 3.6 is 0.24°C. The greatest difference between two consecutive years in the global average since 1901 is 0.29°C between 1976 and 1977, demonstrating the importance of the 0.75°C and 0.74°C temperature increases (the HadCRUT3 linear trend estimates for 1901 to 2005 and 1906 to 2005, respectively) in a centennial time-scale context. However, both trends are small compared with interannual variations at one location, and much smaller than day-to-day variations (Table 3.1).

The principal conclusion from the three global analyses is that the global average surface temperature trend has very likely been slightly more than 0.65°C ± 0.2°C over the period from 1901 to 2005 (Table 3.3), a warming greater than any since at least the 11th century (see Chapter 6). A HadCRUT3 linear trend over the 1906 to 2005 period yields a warming of 0.74°C ± 0.18°C, but this rate almost doubles for the last 50 years (0.64°C ± 0.13°C for 1956 to 2005; see FAQ 3.1). Clearly, the changes are not linear and can also be characterised as level prior to about 1915, a warming to about 1945, levelling out or even a slight decrease until the 1970s, and a fairly linear upward trend since then (Figure 3.6 and FAQ 3.1). Considered this way, the overall warming from the average of the first 50- year period (1850–1899) through 2001 to 2005 is 0.76°C ± 0.19°C. Clearly, the world’s surface temperature has continued to increase since the TAR and the trend when computed in the same way as in the TAR remains 0.6°C over the 20th century. In view of Section 3.2.2.2 and the dominance of the globe by ocean, the influence of urbanisation on these estimates is estimated to be very small. The last 12 complete years (1995– 2006) now contain 11 of the 12 warmest years since 1850, the earliest year for which comparable records are available. Only 1996 is not in this list – replaced by 1990. 2002 to 2005 are the 3rd, 4th, 5th and 2nd warmest years in the series, with 1998 the warmest in HadCRUT3 but with 2005 and 1998 switching order in GISS and NCDC. The HadCRUT3 surface warming trend over 1979 to 2005 was more than 0.16°C per decade, that is, a total warming of 0.44°C ± 0.12°C (the error bars overlap those of NCDC and GISS). During 2001 to 2005, the global average temperature anomaly has been 0.44°C above the 1961– 1990 average. The value for 2006 is close to the 2001 to 2005 average.

3.2.2.7 Spatial Trend Patterns

Figure 3.9. Linear trend of annual temperatures for 1901 to 2005 (left; °C per century) and 1979 to 2005 (right; °C per decade). Areas in grey have insufficient data to produce reliable trends. The minimum number of years needed to calculate a trend value is 66 years for 1901 to 2005 and 18 years for 1979 to 2005. An annual value is available if there are 10 valid monthly temperature anomaly values. The data set used was produced by NCDC from Smith and Reynolds (2005). Trends significant at the 5% level are indicated by white + marks.

Figure 3.9 illustrates the spatial patterns of annual surface temperature changes for 1901 to 2005 and 1979 to 2005, and Figure 3.10 shows seasonal trends for 1979 to 2005. All maps clearly indicate that differences in trends between locations can be large, particularly for shorter time periods. For the century-long period, warming is statistically significant over most of the world’s surface with the exception of an area south of Greenland and three smaller regions over the southeastern USA and parts of Bolivia and the Congo basin. The lack of significant warming at about 20% of the locations (Karoly and Wu, 2005), and the enhanced warming in other places, is likely to be a result of changes in atmospheric circulation (see Section 3.6). Warming is strongest over the continental interiors of Asia and northwestern North America and over some mid-latitude ocean regions of the SH as well as southeastern Brazil. In the recent period, some regions have warmed substantially while a few have cooled slightly on an annual basis (Figure 3.9). Southwest China has cooled since the mid-20th century (Ren et al., 2005), but most of the cooling locations since 1979 have been oceanic and in the SH, possibly through changes in atmospheric and oceanic circulation related to the PDO and SAM (see discussion in Section 3.6.5). Warming dominates most of the seasonal maps for the period 1979 onwards, but weak cooling has affected a few regions, especially the mid-latitudes of the SH oceans, but also over eastern Canada in spring, possibly in relation to the strengthening NAO (see Section 3.6.4, Figure 3.30). Warming in this period was strongest over western North America, northern Europe and China in winter, Europe and northern and eastern Asia in spring, Europe and North Africa in summer and northern North America, Greenland and eastern Asia in autumn (Figure 3.10).

Figure 3.10. Linear trend of seasonal MAM, JJA, SON and DJF temperature for 1979 to 2005 (°C per decade). Areas in grey have insufficient data to produce reliable trends. The minimum number of years required to calculate a trend value is 18. A seasonal value is available if there are two valid monthly temperature anomaly values. The dataset used was produced by NCDC from Smith and Reynolds (2005). Trends significant at the 5% level are indicated by white + marks.

No single location follows the global average, and the only way to monitor the globe with any confidence is to include observations from as many diverse places as possible. The importance of regions without adequate records is determined from complete model reanalysis fields (Simmons et al., 2004). The importance of the missing areas for hemispheric and global averages is incorporated into the errors bars in Figure 3.6 (see Brohan et al., 2006). Error bars are generally larger in the more data-sparse SH than in the NH; they are larger before the 1950s and largest of all in the 19th century.

Figure 3.11 shows annual trends in DTR from 1979 to 2004. The decline in DTR since 1950 reported in the TAR has now ceased, as confirmed by Figure 3.2. Since 1979, daily minimum temperature increased in most areas except western Australia and southern Argentina, and parts of the western Pacific Ocean; and daily maximum temperature also increased in most regions except northern Peru, northern Argentina, northwestern Australia, and parts of the North Pacific Ocean (Vose et al., 2005a). The changes reported here appear inconsistent with Dai et al. (2006) who reported decreasing DTR in the USA, but this arises partly because Dai et al. (2006) included the high DTR years 1976 to 1978. Furthermore, Figure 3.11 is supported by many other recent regional-scale analyses.

Figure 3.11. Linear trend in annual mean DTR for 1979 to 2004 (°C per decade). Grey regions indicate incomplete or missing data (after Vose et al., 2005a).

Changes in cloud cover and precipitation explained up to 80% of the variance in historical DTR series for the USA, Australia, mid-latitude Canada and the former Soviet Union during the 20th century (Dai et al., 1999). Cloud cover accounted for nearly half of the change in the DTR in Fennoscandia during the 20th century (Tuomenvirta et al., 2000). Variations in atmospheric circulation also affect DTR. Changes in the frequency of certain synoptic weather types resulted in a decline in DTR during the cold half-year in the Arctic (Przybylak, 2000). A positive phase of the NAM (see Section 3.6.4) is associated with increased DTR in the northeastern USA and Canada (Wettstein and Mearns, 2002). Variations in sea level pressure patterns and associated changes in cloud cover partially accounted for increasing trends in cold-season DTR in the northwestern USA and decreasing trends in the south-central USA (Durre and Wallace, 2001). The relationship between DTR and anthropogenic forcings is complex, as these forcings can affect atmospheric circulation, as well as clouds through both greenhouse gases and aerosols.

3.3 Changes in Surface Climate: Precipitation, Drought and Surface Hydrology

3.3.1 Background

Temperature changes are one of the more obvious and easily measured changes in climate, but atmospheric moisture, precipitation and atmospheric circulation also change, as the whole system is affected. Radiative forcing alters heating, and at the Earth’s surface this directly affects evaporation as well as sensible heating (see Box 7.1). Further, increases in temperature lead to increases in the moisture-holding capacity of the atmosphere at a rate of about 7% per °C (Section 3.4.2). Together these effects alter the hydrological cycle, especially characteristics of precipitation (amount, frequency, intensity, duration, type) and extremes (Trenberth et al., 2003). In weather systems, convergence of increased water vapour leads to more intense precipitation, but reductions in duration and/or frequency, given that total amounts do not change much. The extremes are addressed in Section 3.8.2.2. Expectations for changes in overall precipitation amounts are complicated by aerosols. Because aerosols block the Sun, surface heating is reduced. Absorption of radiation by some, notably carbonaceous, aerosols directly heats the aerosol layer that may otherwise have been heated by latent heat release following surface evaporation, thereby reducing the strength of the hydrological cycle. As aerosol influences tend to be regional, the net expected effect on p