Anthropogenic warming of central England temperature

Transcription

1 ATMOSPHERIC SCIENCE LETTERS Atmos. Sci. Let. 7: (2006) Published online 18 September 2006 in Wiley InterScience ( Anthropogenic warming of central England temperature David J. Karoly 1 * and Peter A. Stott 2 1 School of Meteorology, University of Oklahoma, Norman, OK 73072, USA 2 Met Office, Hadley Centre for Climate Prediction and Research (Reading Unit), Meteorology Building, University of Reading, Reading RG6 6BB, UK *Correspondence to: David J. Karoly, School of Meteorology, University of Oklahoma, National Weather Center, 120 David L. Boren Blvd., Norman, OK , USA. dkaroly@ou.edu Received: 20 June 2006 Revised: 18 August 2006 Accepted: 21 August 2006 Abstract The variability of central England temperature (CET) at inter annual, decadal and 50-year time scales, as simulated by the HadCM3 model, agrees well with its observed variability over the period The observed warming in annual-mean CET of about 1.0 C since 1950 is very unlikely to be due to natural climate variations and is consistent with the response to anthropogenic (ANT) forcing, demonstrating a significant human influence on this warming. Crown Copyright Reproduced with the permission of the Controller of HMSO. Keywords: climate change; Central England temperature; detection and attribution; climate variability; climate modelling; North Atlantic Oscillation 1. Introduction An anthropogenic climate change signal has been identified in the recent warming of global scale surface temperatures (Stott et al., 2001; Tett et al., 2002) and continental average temperatures (Karoly et al., 2003; Stott, 2003; Zwiers and Zhang, 2003). However, the magnitude of natural climate variability increases relative to any greenhouse-gas-induced warming signal as the area is reduced over which temperatures are averaged, making it more difficult to identify anthropogenic warming at regional scales. The observational record of Central England temperature (CET) is the longest continuous instrumental surface temperature series available, extending from 1659 to the present (Manley, 1974; Parker et al., 1992; Parker and Horton, 2005). Here, we seek to identify an anthropogenic climate change signal for the first time at a small regional scale, in CET, which has shown a marked annual-mean warming of about 1.0 C since We assess whether this warming can be explained by natural internal climate variations and the likely causes of this warming using HadCM3, a coupled ocean-atmosphere general circulation model (Johns et al., 2003). Temperature from a single grid box of size 2.5 latitude by 3.75 longitude over England is used as the model estimate of CET. A critical issue in the detection and attribution of climate change is that climate model simulations provide a reliable estimate of the unforced natural variability of the climate system at multi-decadal time scales. However, the observational record for temperature is generally too short to provide an estimate of natural temperature variability at 30-year or 50-year time scales and hence to be used to evaluate model simulations of variability at those time scales. The CET record is the longest available instrumental record in the world and is used to demonstrate that HadCM3 can reliably simulate natural climate variability at interannual to 50-year time scales. In the next sections, the observational record for CET and the climate model data are described briefly. Then the simulated variability of CET is compared with the observed variability at interannual, decadal and 50-year timescales. Finally, the observed warming in CET over the last 50 years is compared with the model-simulated natural internal variations and the model response to changes in anthropogenic and natural external forcing. 2. Observed Central England temperature The CET record is based on instrument observations at several sites in the midlands of England since 1659 and is the longest available instrumental record of surface air temperature in the world (Manley, 1974; Parker et al., 1992; Parker and Horton, 2005). It is representative of a roughly triangular area of the United Kingdom enclosed by Bristol, Lancashire and London. CET is currently calculated as the average of the surface air temperatures observed at three stations; Pershore, Rothamstead and Stonyhurst, as shown in Figure 1. These stations are chosen to correspond with those used historically from the UK surface station network. The data have been adjusted to ensure consistency with the historical series. Since 1974, the data have been adjusted by C to allow for urban warming (Parker and Horton, 2005). Monthly mean CET data were obtained from the Hadley Centre for Climate Prediction and Research, UK Met Office. From 1700, the monthly mean values are available in tenths of a degree and are considered to be more accurate. The CET observational data have been used from Crown Copyright Reproduced with the permission of the Controller of HMSO.

2 82 D. J. Karoly and P. A. Stott solar irradiance and volcanic aerosol amounts in the stratosphere over the period (NAT runs). 4. Comparison of variability Figure 1. Locations of the three stations currently averaged to provide the Central England temperature, together with the grid box (shaded) from the HadCM3 model used to represent CET, and the outlines of the 8 surrounding grid boxes 3. HadCM3 model The HadCM3 climate model (Johns et al., 2003) is a coupled ocean-atmosphere general circulation model with horizontal resolution of 2.5 latitude by 3.75 longitude in the atmosphere and 1.25 latitude by 1.25 longitude in the ocean. The vertical resolution is 19 levels in the atmosphere and 20 levels in the ocean. It includes representations of important physical processes in the atmosphere and the ocean, as well as sea-ice and land-surface processes. It maintains a stable global-mean climate when external forcings are not varied. The surface air temperature from a single model grid box is used to represent CET in the model, as shown in Figure 1. The variations of the model temperatures at interannual and decadal time scales in all 8 surrounding grid boxes shown in Figure 1 have correlations greater than 0.85 with the temperature variations in the CET grid box, associated with the large spatial coherence of temperature variations at these time scales. This specific grid box is chosen to represent CET because it has a larger fraction of land than the neighbouring grid box to its west. Constant external forcing simulations (control runs) allow the estimation of the natural internal variability of the unforced climate system. A 2400 year control simulation with HadCM3 was available for analysis. Two ensembles of simulations were available to investigate the response of the model to changes in external forcing (Tett et al., 2002; Johns et al., 2003). The first ensemble is a set of four simulations with different initial conditions that include the same observed and estimated changes in concentrations of atmospheric greenhouse gases, ozone and sulphate aerosols over the period (ANT runs) to represent the human influence on climate. The second ensemble of four simulations represents the climate response to natural external forcings, including estimated changes in total The observed annual mean and seasonal mean Central England temperatures were calculated from monthly mean data. For the period from 1700 to 1900, there is likely to be only a very small influence from the climate response due to increasing greenhouse gases, so this period is used to estimate the natural variability of CET. The standard deviations of interannual and decadal variations of observed CET were calculated for the period The standard deviation of the overlapping 50-year in CET during this period was estimated using a sliding 50-year window advancing 20-years for each sample. CET data for 2400 years are available from the HadCM3 control run. The standard deviations of interannual and decadal variations of CET and 50-year were estimated using a sliding 201-year window (the same length as the observational data) advancing 50-years for each sample. The variability of the estimates over the long control run was used to provide 90% confidence intervals for the estimates from a 201-year sample. The comparison of observed and modeled variability of annual mean CET at interannual, decadal and 50-year time scales is shown in Figure 2. A similar comparison of observed and modeled variability of seasonal mean CET is presented in Table I. The model-simulated variability of CET at interannual and decadal timescales agrees very well with the observed CET variability for both annual and seasonal means. The model-simulated variability of annual mean CET at 50-year time scales is slightly larger than the observed variability. For the seasonal means in Table I, the model-simulated variability of 50-year is also slightly larger than observed in all seasons except autumn (SON). The observed variability probably includes some response to natural external forcing variations, such as changes in solar irradiance and volcanic aerosols, which are not included in the control model simulations. Hence, the model-estimated low frequency variability provides a slightly conservative estimate when used for detection and attribution studies, as the model-estimated variability of 50-year is slightly larger than observed, even though it does not include natural external forcing variations. 5. Detection and attribution of the warming trend in CET The observed low frequency variations of CET from 1700 are shown in Figure 3, together with the ensemble average CET variations from the HadCM3 simulations with changes in anthropogenic (ANT) and natural (NAT) forcings. In the observed CET, there

3 Anthropogenic warming of CET 83 Figure 2. Variability of Central England temperature at interannual, decadal and 50-year timescales from observations for and from the HadCM3 control simulation. The 90% confidence intervals for the variability estimated from a 201-year sample are shown by the error bars, based on resampling the model control run Figure 3. Time series of low-pass filtered variations of observed Central England temperature, as anomalies relative to the average for (orange line), for the period Also shown are the ensemble mean CET variations from the HadCM3 simulations with changes in anthropogenic (ANT, red line) and natural (NAT, blue line) climate forcings over is substantial low frequency variability including rapid warming during , but the recent warming is larger and longer duration than any other period in the record. The ensemble mean CET from the simulations with ANT forcing shows a pronounced warming after about 1960 but this starts from a negative anomaly and does not reach the magnitude of the observed warming in The ensemble mean CET from the naturally forced simulations shows warming in the first half of the 20th century, in good agreement with the observations, but shows cooling after about To assess the significance of the recent observed warming in CET, the observed linear in annual-mean CET over the period and are compared with the frequency distribution of 50-year from the HadCM3 control run in Figure 4. The observed warming in annual-mean CET over of about 1.0 Cis significantly larger than due to natural internal climate variations at the 1% level. The observed warming over is slightly smaller and is significant at the 5% level. Hence, the observed annual mean warming trend over the last 50 years is very unlikely to be due to natural internal climate variability alone. The observed 50-year in seasonal CET are compared with the simulated in Table II. The warming trend in CET over is largest Figure 4. Probability distribution of 50-year in Central England temperature from the HadCM3 control simulation (black line), compared with the observed over (orange vertical line) and (yellow vertical line), and the model-simulated for in response to changes in anthropogenic climate forcing (red vertical lines) and in natural external climate forcing (blue vertical lines) in winter (DJF) and is significant at the 5% level in all seasons except autumn (SON). The observed annual and seasonal warming lie within the range of the model-simulated 50-year in CET from the ANT ensemble, except for autumn, and are significantly different from the model-simulated Table I. Variability of Central England temperature at interannual, decadal and 50-year timescales from observations for and from the HadCM3 control simulation. The 90% confidence intervals for the variability estimated from a 201-year sample are indicated for the HadCM3 values, based on resampling the model control run DJF MAM JJA SON Annual Interannual standard deviation: Observed ( C) Interannual standard deviation: HadCM3 ( C) 1.36 ± ± ± ± ± 0.05 Decadal standard deviation: Observed ( C) Decadal standard deviation: HadCM3 ( C) 0.47 ± ± ± ± ± 0.05 Standard deviation of 50-year : Observations ( C) Standard deviation of 50-year : HadCM3 ( C) ± ± ± ± ± 0.024

4 84 D. J. Karoly and P. A. Stott Table II. Seasonal and annual mean 50-year warming in CET from observations and the ensemble-means from the HadCM3 simulations with changes in anthropogenic (ANT) and natural (NAT) climate forcings. The uncertainty ranges for the ensemble mean for forced are estimated to be from the long control run and not from the spread of the ensemble members DJF MAM JJA SON Annual Observed trend ( C/decade) Observed trend ( C/decade) % confidence interval for 50-year from HadCM3 control run ±0.23 ±0.17 ±0.13 ±0.16 ±0.12 HadCM3 ensemble mean trend from ANT runs ( C/decade) 0.20 ± ± ± ± ± 0.06 HadCM3 ensemble mean trend from NAT runs ( C/decade) 0.01 ± ± ± ± ± 0.06 Table III. Annual mean warming in CET over 30-year, 50-year and 100-year intervals from observations and the ensemble-means from the HadCM3 simulations with changes in anthropogenic (ANT) and natural (NAT) climate forcings. The uncertainty ranges for the ensemble mean for forced are estimated from the long control run and not from the spread of the ensemble members 30 year 50-year 100-year Observed trend ending in 1999 ( C/decade) Observed trend ending in 2005 ( C/decade) % confidence interval for from HadCM3 control run ±0.25 ±0.12 ±0.05 HadCM3 ensemble mean trend ending in 1999 from ANT runs ( C/decade) 0.23 ± ± ± 0.02 HadCM3 ensemble mean trend ending in 1999 from NAT runs ( C/decade) 0.01 ± ± ± 0.02 from the NAT ensemble. In autumn, the modelsimulated are larger than in all the other seasons, including winter, in all the ANT ensemble runs. The ensemble-mean warming over in autumns is significantly larger than observed. This is the only season where there is a significant difference between the observed warming and the ensemblemean simulated warming from the ANT ensemble. The reason for this difference is unknown. The significance of the recent trend of observed warming when considered over different trend lengths is assessed in Table III, where linear over 30- year, 50-year and 100-year periods are considered. For all these different trend lengths, the observed warming in annual mean CET have accelerated until 2005 and are significant at more than the 5% level. The significance levels of the warming do not increase when longer trend lengths are considered, probably because of the observed increase in the rate of warming towards the end of the observational record. It should be noted that there are large 30- year warming in the observed CET record in the early 18th and 19th centuries (see Figure 3) that are likely due to natural climate variations and are comparable in magnitude to the observed warming over However, they are smaller than the observed 30-year warming trend to Discussion There is good agreement between the variability and the rate of recent warming of observed CET and that from a single grid box from simulations with the HadCM3 climate model. Given that numerical model simulations are not expected to reliably represent variations on the grid box scale due to their limitations in representing sub-grid scale processes and the limitations of numerical algorithms at the grid box scale, this agreement is remarkable. The large spatial coherence of low frequency temperature variations means that the variations at a single grid box are representative of temperature variations over a much larger area. All nine grid cells shown in Figure 1 have similar low frequency variability and recent warming, and compare well with the observed CET. Another issue is that variations of the North Atlantic Oscillation (NAO) and associated changes in thermal advection contribute to a large fraction of the observed variability of CET in winter. The observed increasing trend in the NAO over may have contributed to some of the warming trend in CET in winter, with one estimate being that 70% of the observed increase in Northern Europe (10W 50E and 50 70N) winter temperatures over that period is due to the strengthening of the NAO (Scaife et al., 2005). Since the observed trend in winter NAO is not simulated well by HadCM3 with changes in ANT forcing, some of the good agreement between the modeled and observed in DJF CET shown in Table II could be fortuitous. However, Table I shows that the winter variability of CET in HadCM3 is slightly larger than that observed at all three time scales considered, indicating that there is a greater confidence in the conclusion of detection of a significant warming trend in DJF CET over (at the 5% level) than in the identification of a human influence in the recent winter warming. Although Table II shows that the ensemble mean model warming in winter over agrees well with the observed warming, this agreement could be misleading if a large part of the observed CET trend was caused by the increase in the NAO.

5 Anthropogenic warming of CET 85 In summary, the observed annual mean warming in CET over the last 30, 50 and 100 years is consistent with the model response to increasing greenhouse gases and aerosols and is not consistent with the response to changes in natural external forcing or to natural internal climate variations. Hence, there is evidence for a significant human influence in the recent warming of annual mean in CET, associated with increasing concentrations of greenhouse gases and aerosols in the atmosphere. The model does not simulate the observed increase in the NAO over and, since the NAO explains a large fraction of the variability in CET in winter, the evidence for a human influence on winter warming is weaker than it is for annual mean warming. Acknowledgements This research was completed in part while DJK was a Visiting Scientist at the Hadley Centre (Reading Unit) in June July DJK was supported by the Gary Comer Science and Education Foundation. PAS was funded by the UK Department for Environment, Food and Rural Affairs under contract PECD 7/12/37. The comments from two anonymous reviewers led to significant improvements in this paper. References 2100 simulated with the HadCM3 model under updated emissions scenarios. Climate Dynamics 20: Karoly DJ, Braganza K, Stott PA, Arblaster J, Meehl G, Broccoli A, Dixon KW Detection of a human influence on North American climate. Science 302: Manley G Central England temperatures: monthly means 1659 to Quarterly Journal of the Royal Meteorological Society 100: Parker DE, Horton B Uncertainties in Central England temperature and some improvements to the maximum and minimum series. International Journal of Climatology 25: Parker DE, Legg TP, Folland CK A new daily central England temperature series. International Journal of Climatology 12: Scaife AA, Knight JR, Vallis GK, Folland CK A stratospheric influence on the winter NAO and North Atlantic surface climate. Geophysical Research Letters 32: L Stott PA Attribution of regional-scale temperature changes to anthropogenic and natural causes. Geophysical Research Letters 30. Doi: /2003GL Stott PA, Tett SFB, Jones GS, Allen MR, Ingram WJ, Mitchell JFB Attribution of twentieth century temperature change to natural and anthropogenic causes. Climate Dynamics 17: Tett SFB, Jones GS, Stott PA, Hill DC, Mitchell JFB, Allen MR, Ingram WJ, Johns TC, Johnson CE, Jones A, Roberts DL, Sexton DMH, Woodage MJ Estimation of natural and anthropogenic contributions to 20th century temperature change. Journal of Geophysical Research 107. Doi: /2000JD Zwiers FW, Zhang X Towards regional scale climate change detection. Journal of Climate 16: Johns TC, Gregory JM, Ingram WJ, Johnson CE, Jones A, Lowe JA, Mitchell JFB, Roberts DL, Sexton DMH, Stevenson DS, Tett SFB, Woodage MJ Anthropogenic climate change for 1860 to