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Peter A. Stott and Simon F. B. Tett

Abstract

Spatially and temporally dependent fingerprint patterns of near-surface temperature change are derived from transient climate simulations of the second Hadley Centre coupled ocean–atmosphere GCM (HADCM2). Trends in near-surface temperature are calculated from simulations in which HADCM2 is forced with historical increases in greenhouse gases only and with both greenhouse gases and anthropogenic sulfur emissions. For each response an ensemble of four simulations is carried out. An estimate of the natural internal variability of the ocean–atmosphere system is taken from a long multicentury control run of HADCM2.

The aim of the study is to investigate the spatial and temporal scales on which it is possible to detect a significant change in climate. Temporal scales are determined by taking temperature trends over 10, 30, and 50 yr using annual mean data, and spatial scales are defined by projecting these trends onto spherical harmonics.

Each fingerprint pattern is projected onto the recent observed pattern to give a scalar detection variable. This is compared with the distribution expected from natural variability, estimated by projecting the fingerprint pattern onto a distribution of patterns taken from the control run. Detection is claimed if the detection variable is greater than the 95th percentile of the distribution expected from natural variability. The results show that climate change can be detected on the global mean scale for 30- and 50-yr trends but not for 10-yr trends, assuming that the model’s estimate of variability is correct. At subglobal scales, climate change can be detected only for 50-yr trends and only for large spatial scales (greater than 5000 km).

Patterns of near-surface temperature trends for the 50 yr up to 1995 from the simulation that includes only greenhouse gas forcing are inconsistent with the observed patterns at small spatial scales (less than 2000 km). In contrast, patterns of temperature trends for the simulation that includes both greenhouse gas and sulfate forcing are consistent with the observed patterns at all spatial scales.

The possible limits to future detectability are investigated by taking one member of each ensemble to represent the observations and other members of the ensemble to represent model realizations of future temperature trends. The results show that for trends to 1995 the probability of detection is greatest at spatial scales greater than 5000 km. As the future signal of climate change becomes larger relative to the noise of natural variability, detection becomes very likely at all spatial scales by the middle of the next century.

The model underestimates climate variability as seen in the observations at spatial scales less than 2000 km. Therefore, some caution must be exercised when interpreting model-based detection results that include a contribution of small spatial scales to the climate change fingerprint.

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Ian A. MacKenzie, Simon F. B. Tett, and Anders V. Lindfors

Abstract

Clear-sky brightness temperature measurements from the High-Resolution Infrared Radiation Sounder (HIRS) are simulated with two climate models via a radiative transfer code. The models are sampled along the HIRS orbit paths to derive diurnal climatologies of simulated brightness temperature analogous to an existing climatology based on HIRS observations. Simulated and observed climatologies are compared to assess model performance and the robustness of the observed climatology.

Over land, there is good agreement between simulations and observations, with particularly high consistency for the tropospheric temperature channels. Diurnal cycles in the middle- and upper-tropospheric water vapor channels are weak in both simulations and observations, but the simulated diurnal brightness temperature ranges are smaller than are observed with different phase and there are also intermodel differences. Over sea, the absence of diurnal variability in the models’ sea surface temperatures causes an underestimate of the small diurnal cycles measured in the troposphere.

The simulated and observed climatologies imply similar diurnal sampling biases in the HIRS record for the tropospheric temperature channels, but for the upper-tropospheric water vapor channel, differences in the contributions of the 24- and 12-hourly diurnal harmonics lead to differences in the implied bias. Comparison of diurnal cycles derived from HIRS-like and full model sampling suggests that the HIRS measurements are sufficient to fully constrain the diurnal behavior.

Overall, the results suggest that recent climate models well represent the major processes driving the diurnal behavior of clear-sky brightness temperature in the HIRS channels. This encourages further studies of observed and simulated climate trends over the HIRS era.

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Matthew Collins, Timothy J. Osborn, Simon F. B. Tett, Keith R. Briffa, and Fritz H. Schweingruber

Abstract

Validation of the decadal to centennial timescale variability of coupled climate models is limited by the scarcity of long observational records. Proxy indicators of climate, such as tree rings, ice cores, etc., can be utilized for this purpose. This study presents a quantitative comparison of the variability of the third version of the Hadley Centre ocean–atmosphere coupled model with a network of temperature-sensitive tree-ring densities covering the northern high latitudes. The tree-ring density records are up to 600 years long, and temperature reconstructions based on two different methods of removing the bias due to changing tree age are used. The first is a standard method that may remove low-frequency variability on timescales of the order of the tree life span (i.e., multidecadal to century timescales). The second (age-band decomposition) maintains low-frequency variability by only comparing similar age tree rings at each site, thus avoiding the need to remove the age effect (but at the cost of greater uncertainty in the earlier years when fewer tree cores are available). The variability of the model control simulation, which represents only the internal variability of the climate system, agrees reasonably well with the tree-ring reconstructions using the standard method at the regional level, although the model may underestimate the variance of mean Northern Hemisphere land temperature by as much as a factor of 1.8 on all timescales if one takes account of the uncertainty in the tree-ring reconstructions. Agreement with the age-band decomposition tree-ring reconstructions is less good with the model underestimating the hemispheric variance by as much as a factor of 2.1 on all timescales and by as much as a factor of 3.0 on decadal to centennial timescales. Underestimation of the natural variability of climate by the model would be serious as it may lead to false detections of climate change or erroneously low uncertainty estimates in future climate predictions. However, it is shown that some of this underestimation may be due to the lack of natural climate forcing in the model control simulation due, for example, to solar variability and volcanic eruptions. The study suggests that further quantification of the uncertainties in the proxy data, and inclusion of natural climate forcings in the model simulations, are important steps in making comparisons of climate models with the proxy record over the last 1000 years.

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Anders V. Lindfors, Ian A. Mackenzie, Simon F. B. Tett, and Lei Shi

Abstract

A climatology of the diurnal cycles of HIRS clear-sky brightness temperatures was developed based on measurements over the period 2002–07. This was done by fitting a Fourier series to monthly gridded brightness temperatures of HIRS channels 1–12. The results show a strong land–sea contrast with stronger diurnal cycles over land, and extending from the surface up to HIRS channel 6 or 5, with regional maxima over the subtropics. Over seas, the diurnal cycles are generally small and therefore challenging to detect. A Monte Carlo uncertainty analysis showed that more robust results are reached by aggregating the data zonally before applying the fit. The zonal fits indicate that small diurnal cycles do exist over sea. The results imply that for a long-lived satellite such as NOAA-14, drift in the overpass time can cause a diurnal sampling bias of more than 5 K for channel 8 (surface and lower troposphere).

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Simon F. B. Tett, Toby J. Sherwin, Amrita Shravat, and Oliver Browne

Abstract

Volume transports from six ocean reanalyses are compared with four sets of in situ observations: across the Greenland–Scotland ridge (GSR), in the Labrador Sea boundary current, in the deep western boundary current at 43°N, and in the Atlantic meridional overturning circulation (AMOC) at 26°N in the North Atlantic. The higher-resolution reanalyses (on the order of ¼° × ¼°) are better at reproducing the circulation pattern in the subpolar gyre than those with lower resolution (on the order of 1°). Simple Ocean Data Assimilation (SODA) and Estimating the Circulation and Climate of the Ocean (ECCO)–Jet Propulsion Laboratory (JPL) produce transports at 26°N that are close to those observed [17 Sv (1 Sv ≡ 106 m3 s−1)]. ECCO, version 2, and SODA produce northward transports across the GSR (observed transport of 8.2 Sv) that are 22% and 29% too big, respectively. By contrast, the low-resolution reanalyses have transports that are either too small [by 31% for ECCO-JPL and 49% for Ocean Reanalysis, system 3 (ORA-S3)] or much too large [Decadal Prediction System (DePreSys)]. SODA had the best simulations of mixed layer depth and with two coarse grid long-term reanalyses (DePreSys and ORA-S3) is used to examine changes in North Atlantic circulation from 1960 to 2008. Its results suggest that the AMOC increased by about 20% at 26°N while transport across the GSR hardly altered. The other (less reliable) long-term reanalyses also had small changes across the GSR but changes of +10% and −20%, respectively, at 26°N. Thus, it appears that changes in the overturning circulation at 26°N are decoupled from the flow across the GSR. It is recommended that transport observations should not be assimilated in ocean reanalyses but used for validation instead.

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Helen M. Hanlon, Gabriele C. Hegerl, Simon F. B. Tett, and Doug M. Smith

Abstract

Daily maximum and minimum summer temperatures have increased throughout the majority of Europe over the past few decades, along with the frequency and intensity of heat waves. It is essential to learn whether this rise is expected to continue in the future for adaptation purposes. A study of predictability of European temperature indices with the Met Office Hadley Centre Decadal Prediction System (DePreSys) has revealed significant skill in predictions of 5- and 10-yr average indices of the summer mean and maximum 5-day average temperatures based on daily maximum and minimum temperatures for a large area of Europe, particularly in the Mediterranean. In contrast, the decadal forecasts of winter mean/minimum 5-day average temperature indices show poorer skill than the summer indices. Significant skill is shown for the United Kingdom in some cases but less than for the European/Mediterranean regions.

Comparison of two parallel ensembles, one initialized with observations and one without initialization, has shown that the skill largely originates from external forcing. However, there were a few cases with hints of additional skill in forecasts of decadal mean indices due to the initialization.

Model realizations of extreme indices can have large biases compared to observations that are different from those of the mean climate indices. Several methods were tested for correcting biases, as well as for testing the significance and quantifying uncertainty of the results to rule out cases of spurious skill. Bias correction of each index individually is required as biases vary across different extremes.

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Jin-Song von Storch, Peter Müller, Ronald J. Stouffer, Reinhard Voss, and Simon F. B. Tett

Abstract

This paper studies the variability of deep-ocean mass transport using four 1000-yr integrations performed with coupled general circulation models. Statistics describing the spectral and spatial features are considered. It is shown that these features depend crucially on the time-mean state. For the transport of tropical and subtropical water masses in three of the integrations, the spectral levels continually increase with decreasing frequency and do not show isolated peaks at low frequencies. The slope of the low-frequency spectrum (in a log–log plot) changes with increasing depth. It has values of about 0 near the surface, about −1 at intermediate depth, and about −2 at or near the bottom. The result indicates that the maximal memory timescale for deep-ocean mass transport is longer than a few centuries. The situation is different in the fourth integration, which has a different mean circulation pattern. In this case, the low-frequency spectrum is more or less flat in the tropical and subtropical oceans below 2000–3000 m, indicating weak low-frequency variations. The dominant spatial covariance structures describe an anomalous recirculation of intermediate water masses, which is confined to a large extent to each ocean basin. The spatial scale of the dominant modes is therefore smaller than that of the time-mean circulation.

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Andrew P. Schurer, Gabriele C. Hegerl, Michael E. Mann, Simon F. B. Tett, and Steven J. Phipps

Abstract

Reconstructions of past climate show notable temperature variability over the past millennium, with relatively warm conditions during the Medieval Climate Anomaly (MCA) and a relatively cold Little Ice Age (LIA). Multimodel simulations of the past millennium are used together with a wide range of reconstructions of Northern Hemispheric mean annual temperature to separate climate variability from 850 to 1950 CE into components attributable to external forcing and internal climate variability. External forcing is found to contribute significantly to long-term temperature variations irrespective of the proxy reconstruction, particularly from 1400 onward. Over the MCA alone, however, the effect of forcing is only detectable in about half of the reconstructions considered, and the response to forcing in the models cannot explain the warm conditions around 1000 CE seen in some reconstructions. The residual from the detection analysis is used to estimate internal variability independent from climate modeling, and it is found that the recent observed 50- and 100-yr hemispheric temperature trends are substantially larger than any of the internally generated trends even using the large residuals over the MCA. Variations in solar output and explosive volcanism are found to be the main drivers of climate change from 1400 to 1900, but for the first time a significant contribution from greenhouse gas variations to the cold conditions during 1600–1800 is also detected. The proxy reconstructions tend to show a smaller forced response than is simulated by the models. This discrepancy is shown, at least partly, to be likely associated with the difference in the response to large volcanic eruptions between reconstructions and model simulations.

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Simon F. B. Tett, Daniel J. Rowlands, Michael J. Mineter, and Coralia Cartis

Abstract

A large number of perturbed-physics simulations of version 3 of the Hadley Centre Atmosphere Model (HadAM3) were compared with the Clouds and the Earth's Radiant Energy System (CERES) estimates of outgoing longwave radiation (OLR) and reflected shortwave radiation (RSR) as well as OLR and RSR from the earlier Earth Radiation Budget Experiment (ERBE) estimates. The model configurations were produced from several independent optimization experiments in which four parameters were adjusted. Model–observation uncertainty was estimated by combining uncertainty arising from satellite measurements, observational radiation imbalance, total solar irradiance, radiative forcing, natural aerosol, internal climate variability, and sea surface temperature and that arising from parameters that were not varied. Using an emulator built from 14 001 “slab” model evaluations carried out using the climateprediction.net ensemble, the climate sensitivity for each configuration was estimated. Combining different prior probabilities for model configurations with the likelihood for each configuration and taking account of uncertainty in the emulated climate sensitivity gives, for the HadAM3 model, a 2.5%–97.5% range for climate sensitivity of 2.7–4.2 K if the CERES observations are correct. If the ERBE observations are correct, then they suggest a larger range, for HadAM3, of 2.8–5.6 K. Amplifying the CERES observational covariance estimate by a factor of 20 brings CERES and ERBE estimates into agreement. In this case the climate sensitivity range is 2.7–5.4 K. The results rule out, at the 2.5% level for HadAM3 and several different prior assumptions, climate sensitivities greater than 5.6 K.

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Simon F. B. Tett, Michael J. Mineter, Coralia Cartis, Daniel J. Rowlands, and Ping Liu

Abstract

Perturbed physics configurations of version 3 of the Hadley Centre Atmosphere Model (HadAM3) driven with observed sea surface temperatures (SST) and sea ice were tuned to outgoing radiation observations using a Gauss–Newton line search optimization algorithm to adjust the model parameters. Four key parameters that previous research found affected climate sensitivity were adjusted to several different target values including two sets of observations. The observations used were the global average reflected shortwave radiation (RSR) and outgoing longwave radiation (OLR) from the Clouds and the Earth's Radiant Energy System instruments combined with observations of ocean heat content. Using the same method, configurations were also generated that were consistent with the earlier Earth Radiation Budget Experiment results. Many, though not all, tuning experiments were successful, with about 2500 configurations being generated and the changes in simulated outgoing radiation largely due to changes in clouds. Clear-sky radiation changes were small, largely due to a cancellation between changes in upper-tropospheric relative humidity and temperature. Changes in other climate variables are strongly related to changes in OLR and RSR particularly on large scales. There appears to be some equifinality with different parameter configurations producing OLR and RSR values close to observed values. These models have small differences in their climatology with the one group being similar to the standard configuration and the other group drier in the tropics and warmer everywhere.

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