Sensitivity of sea ice to wind-stress and radiative forcing since 1500: a model study of the Little Ice Age and beyond

Three different reconstructed wind-stress fields which take into account variations of the North Atlantic Oscillation, one general circulation model wind-stress field, and three radiative forcings (volcanic activity, insolation changes and greenhouse gas changes) are used with the UVic Earth System Climate Model to simulate the surface air temperature, the sea-ice cover, and the Atlantic meridional overturning circulation (AMOC) since 1500, a period which includes the Little Ice Age (LIA). The simulated Northern Hemisphere surface air temperature, used for model validation, agrees well with several temperature reconstructions. The simulated sea-ice cover in each hemisphere responds quite differently to the forcings. In the Northern Hemisphere, the simulated sea-ice area and volume during the LIA are larger than the present-day area and volume. The wind-driven changes in sea-ice area are about twice as large as those due to thermodynamic (i.e., radiative) forcing. For the sea-ice volume, changes due to wind forcing and thermodynamics are of similar magnitude. Before 1850, the simulations suggest that volcanic activity was mainly responsible for the thermodynamically produced area and volume changes, while after 1900 the slow greenhouse gas increase was the main driver of the sea-ice changes. Changes in insolation have a small effect on the sea ice throughout the integration period. The export of the thicker sea ice during the LIA has no significant effect on the maximum strength of the AMOC. A more important process in altering the maximum strength of the AMOC and the sea-ice thickness is the wind-driven northward ocean heat transport. In the Southern Hemisphere, there are no visible long-term trends in the simulated sea-ice area or volume since 1500. The wind-driven changes are roughly four times larger than those due to radiative forcing. Prior to 1800, all the radiative forcings could have contributed to the thermodynamically driven changes in area and volume. In the 1800s the volcanic forcing was dominant, and during the first part of the 1900s both the insolation changes and the greenhouse gas forcing are responsible for thermodynamically produced changes. Finally, in the latter part of the 1900s the greenhouse gas forcing is the dominant factor in determining the sea-ice changes in the Southern Hemisphere.

Optimal filtering for Bayesian detection and attribution of climate change

In the conventional approach to the detection of an anthropogenic or other externally forced climate change signal, optimal filters (fingerprints) are used to maximize the ratio of the observed climate change signal to the natural variability noise. If detection is successful, attribution of the observed climate change to the hypothesized forcing mechanism is carried out in a second step by comparing the observed and predicted climate change signals. In contrast, the Bayesian approach to detection and attribution makes no distinction between detection and attribution. The purpose of filtering in this case is to maximize the impact of the evidence, the observed climate change, on the prior probability that the hypothesis of an anthropogenic origin of the observed signal is true. Whereas in the conventional approach model uncertainties have no direct impact on the definition of the optimal detection fingerprint, in optimal Bayesian filtering they play a central role. The number of patterns retained is governed by the magnitude of the predicted signal relative to the model uncertainties, defined in a pattern space normalized by the natural climate variability. Although this results in some reduction of the original phase space, this is not the primary objective of Bayesian filtering, in contrast to the conventional approach, in which dimensional reduction is a necessary prerequisite for enhancing the signal-to-noise ratio. The Bayesian filtering method is illustrated for two anthropogenic forcing hypotheses: greenhouse gases alone, and a combination of greenhouse gases plus sulfate aerosols. The hypotheses are tested against 31-year trends for near-surface temperature, summer and winter diurnal temperature range, and precipitation. Between six and thirteen response patterns can be retained, as compared with the one or two response patterns normally used in the conventional approach. Strong evidence is found for the detection of an anthropogenic climate change in temperature, with some preference given to the combined forcing hypothesis. Detection of recent anthropogenic trends in diurnal temperature range and precipitation is not successful, but there remains strong net evidence for anthropogenic climate change if all data are considered jointly.

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Simulated climate change during the last 1,000 years: comparing the ECHO-G general circulation model with the MAGICC simple climate model

An intercomparison of eight climate simulations, each driven with estimated natural and anthropogenic forcings for the last millennium, indicates that the so-called “Erik” simulation of the ECHO-G coupled ocean-atmosphere climate model exhibits atypical behaviour. The ECHO-G simulation has a much stronger cooling trend from 1000 to 1700 and a higher rate of warming since 1800 than the other simulations, with the result that the overall amplitude of millennial-scale temperature variations in the ECHO-G simulation is much greater than in the other models. The MAGICC (Model for the Assessment of Greenhouse-gas-Induced Climate Change) simple climate model is used to investigate possible causes of this atypical behaviour. It is shown that disequilibrium in the initial conditions probably contributes spuriously to the cooling trend in the early centuries of the simulation, and that the omission of tropospheric sulphate aerosol forcing is the likely explanation for the anomalously large recent warming. The simple climate model results are used to adjust the ECHO-G Erik simulation to mitigate these effects, which brings the simulation into better agreement with the other seven models considered here and greatly reduces the overall range of temperature variations during the last millennium simulated by ECHO-G. Smaller inter-model differences remain which can probably be explained by a combination of the particular forcing histories and model sensitivities of each experiment. These have not been investigated here, though we have diagnosed the effective climate sensitivity of ECHO-G to be 2.39±0.11 K for a doubling of CO₂.     

Simple indices of global climate variability and change Part II: attribution of climate change during the twentieth century

Five simple indices of surface temperature are used to investigate the influence of anthropogenic and natural (solar irradiance and volcanic aerosol) forcing on observed climate change during the twentieth century. These indices are based on spatial fingerprints of climate change and include the global-mean surface temperature, the land-ocean temperature contrast, the magnitude of the annual cycle in surface temperature over land, the Northern Hemisphere meridional temperature gradient and the hemispheric temperature contrast. The indices contain information independent of variations in global-mean temperature for unforced climate variations and hence, considered collectively, they are more useful in an attribution study than global mean surface temperature alone. Observed linear trends over 1950–1999 in all the indices except the hemispheric temperature contrast are significantly larger than simulated changes due to internal variability or natural (solar and volcanic aerosol) forcings and are consistent with simulated changes due to anthropogenic (greenhouse gas and sulfate aerosol) forcing. The combined, relative influence of these different forcings on observed trends during the twentieth century is investigated using linear regression of the observed and simulated responses of the indices. It is found that anthropogenic forcing accounts for almost all of the observed changes in surface temperature during 1946–1995. We found that early twentieth century changes (1896–1945) in global mean temperature can be explained by a combination of anthropogenic and natural forcing, as well as internal climate variability. Estimates of scaling factors that weight the amplitude of model simulated signals to corresponding observed changes using a combined normalized index are similar to those calculated using more complex, optimal fingerprint techniques.     

Will the tropical land biosphere dominate the climate–carbon cycle feedback during the twenty-first century?

Global warming caused by anthropogenic CO₂ emissions is expected to reduce the capability of the ocean and the land biosphere to take up carbon. This will enlarge the fraction of the CO₂ emissions remaining in the atmosphere, which in turn will reinforce future climate change. Recent model studies agree in the existence of such a positive climate–carbon cycle feedback, but the estimates of its amplitude differ by an order of magnitude, which considerably increases the uncertainty in future climate projections. Therefore we discuss, in how far a particular process or component of the carbon cycle can be identified, that potentially contributes most to the positive feedback. The discussion is based on simulations with a carbon cycle model, which is embedded in the atmosphere/ocean general circulation model ECHAM5/MPI-OM. Two simulations covering the period 1860–2100 are conducted to determine the impact of global warming on the carbon cycle. Forced by historical and future carbon dioxide emissions (following the scenario A2 of the Intergovernmental Panel on Climate Change), they reveal a noticeable positive climate–carbon cycle feedback, which is mainly driven by the tropical land biosphere. The oceans contribute much less to the positive feedback and the temperate/boreal terrestrial biosphere induces a minor negative feedback. The contrasting behavior of the tropical and temperate/boreal land biosphere is mostly attributed to opposite trends in their net primary productivity (NPP) under global warming conditions. As these findings depend on the model employed they are compared with results derived from other climate–carbon cycle models, which participated in the Coupled Climate–Carbon Cycle Model Intercomparison Project (C4MIP).

Transient simulation of the last glacial inception. Part I: glacial inception as a bifurcation in the climate system

We study the mechanisms of glacial inception by using the Earth system model of intermediate complexity, CLIMBER-2, which encompasses dynamic modules of the atmosphere, ocean, biosphere and ice sheets. Ice-sheet dynamics are described by the three-dimensional polythermal ice-sheet model SICOPOLIS. We have performed transient experiments starting at the Eemiam interglacial, at 126 ky BP (126,000 years before present). The model runs for 26 kyr with time-dependent orbital and CO₂ forcings. The model simulates a rapid expansion of the area covered by inland ice in the Northern Hemisphere, predominantly over Northern America, starting at about 117 kyr BP. During the next 7 kyr, the ice volume grows gradually in the model at a rate which corresponds to a change in sea level of 10 m per millennium. We have shown that the simulated glacial inception represents a bifurcation transition in the climate system from an interglacial to a glacial state caused by the strong snow-albedo feedback. This transition occurs when summer insolation at high latitudes of the Northern Hemisphere drops below a threshold value, which is only slightly lower than modern summer insolation. By performing long-term equilibrium runs, we find that for the present-day orbital parameters at least two different equilibrium states of the climate system exist—the glacial and the interglacial; however, for the low summer insolation corresponding to 115 kyr BP, we find only one, glacial, equilibrium state, while for the high summer insolation corresponding to 126 kyr BP only an interglacial state exists in the model.

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Biogeophysical impacts of land use on present-day climate: near-surface temperature change and radiative forcing

Changes in land cover affect climate through the surface energy and moisture budgets, but these biogeophysical impacts of land use have not yet been included in General Circulation Model (GCM) simulations of 20th century climate change. Here, the importance of these effects was assessed by comparing climate simulations performed with current and potential natural vegetation. The northern mid-latitude agricultural regions were simulated to be approximately 1–2 K cooler in winter and spring in comparison with their previously forested state, due to deforestation increasing the surface albedo by approximately 0.1 during periods of snow cover. Some other regions such as the Sahel and India experienced a small warming due to land use. Although the annual mean global temperature is only 0.02 K lower in the simulation with present-day land use, the more local temperature changes in some regions are of a similar magnitude to those observed since 1860. The global mean radiative forcing by anthropogenic surface albedo change relative to the natural state is simulated to be −0.2 Wm², which is comparable with the estimated forcings relative to pre-industrial times by changes in stratospheric and tropospheric ozone, N₂O, halocarbons, and the direct effect of anthropogenic aerosols. Since over half of global deforestation has occurred since 1860, simulations of climate since that date should include the biogeophysical effects of land use.     

Multi-century simulations with the coupled GISS–HYCOM climate model: control experiments

Multi-century climate simulations obtained with the GISS atmospheric general circulation model coupled to the hybrid-isopycnic ocean model HYCOM are described. Greenhouse gas concentrations are held fixed in these experiments to investigate the coupled model’s ability to reproduce the major features of today’s climate with minimal drift. Emphasis is placed on the realism of the oceanic general circulation and its effect on air–sea exchange processes. Several model runs using different closures for turbulent vertical exchange as well as improvements to reduce vertical numerical diffusion are compared with climate observations. As in previous studies, the Southern Ocean emerges as the Achilles Heel of the ocean model; deficiencies in its physical representation had far-reaching consequences in early experiments with the coupled model and have provided the strongest impetus for model improvement. The overarching goal of this work is to add diversity to the pool of ocean models available for climate prediction and thereby reduce biases that may stand in the way of assessing climate prediction uncertainty.

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Sensitivity of global warming to the pattern of tropical ocean warming

The current generations of climate models are in substantial disagreement as to the projected patterns of sea surface temperatures (SSTs) in the Tropics over the next several decades. We show that the spatial patterns of tropical ocean temperature trends have a strong influence on global mean temperature and precipitation and on global mean radiative forcing. We identify the SST patterns with the greatest influence on the global mean climate and find very different, and often opposing, sensitivities to SST changes in the tropical Indian and West Pacific Oceans. Our work stresses the need to reduce climate model biases in these sensitive regions, as they not only affect the regional climates of the nearby densely populated continents, but also have a disproportionately large effect on the global climate.

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Climate simulations for 1880–2003 with GISS modelE

We carry out climate simulations for 1880–2003 with GISS modelE driven by ten measured or estimated climate forcings. An ensemble of climate model runs is carried out for each forcing acting individually and for all forcing mechanisms acting together. We compare side-by-side simulated climate change for each forcing, all forcings, observations, unforced variability among model ensemble members, and, if available, observed variability. Discrepancies between observations and simulations with all forcings are due to model deficiencies, inaccurate or incomplete forcings, and imperfect observations. Although there are notable discrepancies between model and observations, the fidelity is sufficient to encourage use of the model for simulations of future climate change. By using a fixed well-documented model and accurately defining the 1880–2003 forcings, we aim to provide a benchmark against which the effect of improvements in the model, climate forcings, and observations can be tested. Principal model deficiencies include unrealistically weak tropical El Nino-like variability and a poor distribution of sea ice, with too much sea ice in the Northern Hemisphere and too little in the Southern Hemisphere. Greatest uncertainties in the forcings are the temporal and spatial variations of anthropogenic aerosols and their indirect effects on clouds. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Contributions of solar and greenhouse gases forcing during the present warm period

Due to the dramatic increase in the global mean surface temperature (GMST) during the twentieth century, the climate science community has endeavored to determine which mechanisms are responsible for global warming. By analyzing a millennium simulation (the period of 1000–1990 ad) of a global climate model and global climate proxy network dataset, we estimate the contribution of solar and greenhouse gas forcings on the increase in GMST during the present warm period (1891–1990 ad). Linear regression analysis reveals that both solar and greenhouse gas forcing considerably explain the increase in global mean temperature during the present warm period, respectively, in the global climate model. Using the global climate proxy network dataset, on the other hand, statistical approach suggests that the contribution of greenhouse gas forcing is slightly larger than that of solar forcing to the increase in global mean temperature during the present warm period. Overall, our result indicates that the solar forcing as well as the anthropogenic greenhouse gas forcing plays an important role to increase the global mean temperature during the present warm period.     

Cycles and shifts: 1,300 years of multi-decadal temperature variability in the Gulf of Alaska

The Gulf of Alaska (GOA) is highly sensitive to shifts in North Pacific climate variability. Here we present an extended tree-ring record of January–September GOA coastal surface air temperatures using tree-ring width data from coniferous trees growing in the mountain ranges along the GOA. The reconstruction (1514–1999), based on living trees, explains 44% of the temperature variance, although, as the number of chronologies decreases back in time, this value decreases to, and remains around ∼30% before 1840. Verification of the calibrated models is, however, robust. Utilizing sub-fossil wood, we extend the GOA reconstruction back to the early eighth century. The GOA reconstruction correlates significantly (95% CL) with both the Pacific Decadal Oscillation Index (0.53) and North Pacific Index (−0.42) and therefore likely yields important information on past climate variability in the North Pacific region. Intervention analysis on the GOA reconstruction identifies the known twentieth century climate shifts around the 1940s and 1970s, although the mid-1920s shift is only weakly expressed. In the context of the full 1,300 years record, the well studied 1976 shift is not unique. Multi-taper method spectral analysis shows that the spectral properties of the living and sub-fossil data are similar, with both records showing significant (95% CL) spectral peaks at ∼9–11, 13–14 and 18–19 years. Singular spectrum analysis identifies (in order of importance) significant oscillatory modes at 18.7, 50.4, 38.0, 91.8, 24.4, 15.3 and 14.1 years. The amplitude of these modes varies through time. It has been suggested (Minobe in Geophys Res Lett 26:855–858, 1999) that the regime shifts during the twentieth century can be explained by the interaction between pentadecadal (50.4 years) and bidecadal (18.7 years) oscillatory modes. Removal of these two modes of variance from our GOA time series does indeed remove the twentieth century shifts, but many are still identified prior to the twentieth century. Our analysis suggests that climate variability of the GOA is very complex, and that much more work is required to understand the underlying oscillatory behavior that is observed in instrumental and proxy records from the North Pacific region.

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The influence of sea surface temperature anomalies on low-frequency variability of the North Atlantic Oscillation

The influence of sea surface temperature anomalies (SSTA) on multi-year persistence of the North Atlantic Oscillation (NAO) during the second half of the twentieth century is investigated using the Center for Ocean-Land-Atmosphere Studies (COLA) Atmospheric GCM (AGCM) with an emphasis on isolating the geographic location of the SSTA that produce this influence. The present study focuses on calculating the atmospheric response to the SSTA averaged over 1988–1995 (1961–1968) corresponding to the observed period of strong persistence of the positive (negative) phase of the decadal NAO. The model response to the global 1988–1995 average SSTA shows a statistically significant large-scale pattern characteristic of the positive phase of the NAO. Forcing with the global 1961–1968 average SSTA generates a NAO of the opposite polarity compared to observations. However, all large-scale features both in the model and observations during this period are weaker in magnitude and less significant compared to 1988–1995. Additional idealized experiments show that over the northern center of the NAO the non-linear component of the forced response appears to be quite important and acts to enhance the positive NAO signal. On the other hand, over the southern center where the model response is the strongest, it is also essentially linear. The 1988–1995 average SSTA restricted to the western tropical Pacific region produce a positive NAO remarkably similar in structure but stronger in magnitude than the model response to the global and tropical Indo-Pacific 1988–1995 forcing. A 200-hPa geopotential height response in these experiments shows a positive anomaly over the southern center of the NAO embedded in the Rossby wave trains propagating from the western tropical Pacific. Indian Ocean SSTA lead to much weaker positive NAO primarily through the effect on its northern center. SST forcing confined to the North Atlantic north of equator does not produce a response statistically different from the control simulation, suggesting that it is not strong enough to significantly affect the phase of the decadal NAO. Inclusion of the South Atlantic north of 45° south does not change this result.

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Future changes in cyclone climatology over Europe as inferred from a regional climate simulation

This study analyzes the cyclone climatology in regional climate model simulations of present day (1961–1990) and future (2071–2100, A2 and B2 emission scenarios) european climate conditions. The model domain covers the area from Scandinavia to Northern Africa and from the Eastern Atlantic to Russia at a horizontal grid spacing of 50 km. Compared to present day, in the A2 and B2 scenario conditions the annual average storm track intensity increases over the North-East Atlantic and decreases over Russia and the Eastern Mediterranean region. This overall change pattern is larger in the A2 than in the B2 simulations. However, the cyclone climatology change signal shows a large intermonthly variability and important differences across European regions. The largest changes are found over the North-East Atlantic, where the storm track intensity increases in winter and decreases in summer. A significant reduction of storm track intensity is found during late summer and autumn over the Mediterranean region, and from October to January over Russia. The number of cyclones decreases in future conditions throughout Europe, except over the Central Europe and Mediterranean regions in summer (where it increases). The frequency of intense cyclones and the depth of extreme cyclones increase over the North-East Atlantic, decrease over Russia and show an irregular response over the rest of the domain.

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The role of ENSO in global ocean temperature changes during 1955–2011 simulated with a 1D climate model

Global average ocean temperature variations to 2,000 m depth during 1955–2011 are simulated with a 40 layer 1D forcing-feedback-mixing model for three forcing cases. The first case uses standard anthropogenic and volcanic external radiative forcings. The second adds non-radiative internal forcing (ocean mixing changes initiated in the top 200 m) proportional to the Multivariate ENSO Index (MEI) to represent an internal mode of natural variability. The third case further adds ENSO-related radiative forcing proportional to MEI as a possible natural cloud forcing mechanism associated with atmospheric circulation changes. The model adjustable parameters are net radiative feedback, effective diffusivities, and internal radiative (e.g., cloud) and non-radiative (ocean mixing) forcing coefficients at adjustable time lags. Model output is compared to Levitus ocean temperature changes in 50 m layers during 1955–2011 to 700 m depth, and to lag regression coefficients between satellite radiative flux variations and sea surface temperature between 2000 and 2010. A net feedback parameter of 1.7Wm^?2 K^?1 with only anthropogenic and volcanic forcings increases to 2.8Wm^?2 K^?1 when all ENSO forcings (which are one-third radiative) are included, along with better agreement between model and observations. The results suggest ENSO can influence multi-decadal temperature trends, and that internal radiative forcing of the climate system affects the diagnosis of feedbacks. Also, the relatively small differences in model ocean warming associated with the three cases suggests that the observed levels of ocean warming since the 1950s is not a very strong constraint on our estimates of climate sensitivity.     

Internal variability,external forcing and climate trends in multi-decadal AGCM ensembles

An atmospheric general circulation model of intermediate complexity is used to investigate the origin and structure of the climate change in the second half of the twentieth century. The variability of the atmospheric flow is considered as a superposition of an internal part, due to intrinsic dynamical variability, and an external part, due to the variations of the sea surface temperature (SST) forcing. The two components are identified by performing a 50-member ensemble of atmospheric simulations with prescribed, observed SSTs in the period 1949–2002. The large number of realizations allows the estimation of statistics of the atmospheric variability with a high confidence level. The analysis performed focuses on interdecadal and interannual variability of 500 hPa geopotential height in the Northern Hemisphere (NH) during winter. The model reproduces well the structure of the observed trend (defined as the difference in the two 25-year intervals 1977–2001 and 1952–1976), particularly in the Pacific region, and about half of the amplitude of the signal. The trend in 500 hPa height projects mainly onto the second empirical orthogonal function (EOF), both in the observations and in the model ensemble. However, differences between the modelled and the observed variability are found in the pattern of the second EOF in the Atlantic sector. SST changes associated with the El Niño southern oscillation (ENSO) are responsible for about 50% of the signal of the 500 hPa height trend in the Pacific. A second 50-member ensemble is used to evaluate the sensitivity of interdecadal variability to an increase in CO₂ optical depth compatible with observed concentration changes. In this second experiment, the simulated trend includes a statistically significant contribution from the positive phase of the Arctic oscillation (AO). Such a contribution is also found in observations. Furthermore, the additional CO₂ forcing accounts for part of the NH trend in near-surface temperature, and brings the zonal-mean temperature changes in the stratosphere and upper-troposphere closer to observations.

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Spectrothermography of carbonaceous particles

Spectrothermography, defined as the evaluation of thermograms of carbon evolved from heated aerosol samples, is a technique for evaluating differences in particle characteristics as they relate to emission sources and processes that modify particle evolution. Here we describe the inherent uncertainties and demonstrate the utility of this technique with an evaluation of samples that were collected with eight stage cascade impactors at three sites in Mexico City over a period of 5 months. The study was implemented with statistical analysis based on tests for goodness of fit to separate thermograms with distinctive shapes related to the relative amounts of organic and elemental carbon mass that evolves as a function of temperature. Thermograms with unique shapes were found for particles with aerodynamic diameters of 1–10, 0.56–1, 0.32–0.56 and 0.18–0.32 μm with further differentiation of curves related to the relative amounts of gasoline and diesel fuel that was combusted in the region of the three sites. The common shapes fit 32–42% of samples in each particle size range and indicate that this type of analysis can help distinguish differences in the primary sources of organic and elemental carbon.

Evidence for the role of the Atlantic multidecadal oscillation and the ocean heat uptake in hiatus prediction

The recent hiatus in global temperature at the surface has been analysed by several studies, mainly using global climate models. The common accepted picture is that since the late 1990s, the increase in anthropogenic radiative forcings has been counterbalanced by other factors, e.g., a decrease in natural forcings, augmented ocean heat storage and negative phases of ocean–atmosphere-coupled oscillation patterns. Here, simple vector autoregressive models are used for forecasting the temperature hiatus in the period 2001–2014. This gives new insight into the problem of understanding the ocean contribution (in terms of heat uptake and atmosphere–ocean-coupled oscillations) to the appearance of this recent hiatus. In particular, considering data about the ocean heat content until a depth of 700 m and the Atlantic multidecadal oscillation is necessary for correctly forecasting the hiatus, so catching both trend and interannual variability. Our models also show that the ocean heat uptake is substantially driven by the natural component of the total radiative forcing at a decadal time scale, confining the importance of the anthropogenic influences to a longer range warming of the ocean.     

Multi-fingerprint detection and attribution analysis of greenhouse gas, greenhouse gas-plus-aerosol and solar forced climate change

 A multi-fingerprint analysis is applied to the detection and attribution of anthropogenic climate change. While a single fingerprint is optimal for the detection of climate change, further tests of the statistical consistency of the detected climate change signal with model predictions for different candidate forcing mechanisms require the simultaneous application of several fingerprints. Model-predicted climate change signals are derived from three anthropogenic global warming simulations for the period 1880 to 2049 and two simulations forced by estimated changes in solar radiation from 1700 to 1992. In the first global warming simulation, the forcing is by greenhouse gas only, while in the remaining two simulations the direct influence of sulfate aerosols is also included. From the climate change signals of the greenhouse gas only and the average of the two greenhouse gas-plus-aerosol simulations, two optimized fingerprint patterns are derived by weighting the model-predicted climate change patterns towards low-noise directions. The optimized fingerprint patterns are then applied as a filter to the observed near-surface temperature trend patterns, yielding several detection variables. The space-time structure of natural climate variability needed to determine the optimal fingerprint pattern and the resultant signal-to-noise ratio of the detection variable is estimated from several multi-century control simulations with different CGCMs and from instrumental data over the last 136 y. Applying the combined greenhouse gas-plus-aerosol fingerprint in the same way as the greenhouse gas only fingerprint in a previous work, the recent 30-y trends (1966–1995) of annual mean near surface temperature are again found to represent a significant climate change at the 97.5% confidence level. However, using both the greenhouse gas and the combined forcing fingerprints in a two-pattern analysis, a substantially better agreement between observations and the climate model prediction is found for the combined forcing simulation. Anticipating that the influence of the aerosol forcing is strongest for longer term temperature trends in summer, application of the detection and attribution test to the latest observed 50-y trend pattern of summer temperature yielded statistical consistency with the greenhouse gas-plus-aerosol simulation with respect to both the pattern and amplitude of the signal. In contrast, the observations are inconsistent with the greenhouse-gas only climate change signal at a 95% confidence level for all estimates of climate variability. The observed trend 1943–1992 is furthermore inconsistent with a hypothesized solar radiation change alone at an estimated 90% confidence level. Thus, in contrast to the single pattern analysis, the two pattern analysis is able to discriminate between different forcing hypotheses in the observed climate change signal. The results are subject to uncertainties associated with the forcing history, which is poorly known for the solar and aerosol forcing, the possible omission of other important forcings, and inevitable model errors in the computation of the response to the forcing. Further uncertainties in the estimated significance levels arise from the use of model internal variability simulations and relatively short instrumental observations (after subtraction of an estimated greenhouse gas signal) to estimate the natural climate variability. The resulting confidence limits accordingly vary for different estimates using different variability data. Despite these uncertainties, however, we consider our results sufficiently robust to have some confidence in our finding that the observed climate change is consistent with a combined greenhouse gas and aerosol forcing, but inconsistent with greenhouse gas or solar forcing alone. Received: 28 April 1996 / Accepted: 27 January 1997     

On summing the components of radiative forcing of climate change

 Radiative forcing is a useful concept in determining the potential influence of a particular mechanism of climate change. However, due to the increased number of forcing agents identified over the past decade, the total radiative forcing is difficult to assess. By assigning a range of probability distribution functions to the individual radiative forcings and using a Monte-Carlo approach, we estimate the total radiative forcing since pre-industrial times including all quantitative radiative forcing estimates to date. The resulting total radiative forcing has a 75–97% probability of being positive (or similarly a 3–25% probability of being negative), with mean radiative forcing ranging from +0.68 to +1.34 W m⁻², and median radiative forcing ranging from +0.94 to +1.39 W m⁻². Received: 14 March 2001 / Accepted: 1 June 2001