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Twentieth century climate model response and climate sensitivity

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Abstract

Climate forcing and climate sensitivity are two key factors in understanding Earth's climate. There is considerable interest in decreasing our uncertainty in climate sensitivity. This study explores the role of these two factors in climate simulations of the 20th century. It is found that the total anthropogenic forcing for a wide range of climate models differs by a factor of two and that the total forcing is inversely correlated to climate sensitivity. Much of the uncertainty in total anthropogenic forcing derives from a threefold range of uncertainty in the aerosol forcing used in the simulations.
Twentieth century climate model response and climate sensitivity
Jeffrey T. Kiehl
1
Received 19 July 2007; revised 30 August 2007; accepted 13 September 2007; published 28 November 2007.
[1] Climate forcing and climate sensitivity are two key
factors in understanding Earth’s climate. There is
considerable interest in decreasing our uncertainty in
climate sensitivity. This study explores the role of these
two factors in climate simulations of the 20th century. It is
found that the total anthropogenic forcing for a wide range
of climate models differs by a factor of two and that the total
forcing is inversely correlated to climate sensitivity. Much
of the uncertainty in total anthropogenic forcing derives
from a threefold range of uncertainty in the aerosol forcing
used in the simulations. Citation: Kiehl, J. T. (2007),
Twentieth century climate model response and climate
sensitivity, Geophys. Res. Lett.,34, L22710, doi:10.1029/
2007GL031383.
1. Introduction
[2] Understanding the climate of the past is an important
aspect to our ability to predict Earth’s future climate. Three
dimensional global climate models are the most compre-
hensive tools available to simulate Earth’s past, present and
future climates. Methods of testing these models with
observations form an important part of model development
and application. Over the past decade one such test is our
ability to simulate the global anomaly in surface air tem-
perature for the 20th century. A number of observational
reconstructions of the temporal evolution of this climatically
important quantity have been created [Jones et al., 1999].
Climate model simulations of the 20th century can be
compared in terms of their ability to reproduce this temper-
ature record. This is now an established necessary test for
global climate models. Of course this is not a sufficient test
of these models and other metrics should be used to test
models, for example the ability to simulate the evolution of
ocean heat uptake over the later part of the 20th century
[Levitus et al., 2001; Barnett et al., 2001], or a models
ability to simulate trends in various modes of variability. All
of these can be viewed as necessary test for climate models.
[3] A review of the published literature on climate
simulations of the 20th century indicates that a large number
of fully coupled three dimensional climate models are able
to simulate the global surface air temperature anomaly with
a good degree of accuracy [Houghton et al., 2001]. For
example all models simulate a global warming of 0.5 to
0.7°C over this time period to within 25% accuracy. This is
viewed as a reassuring confirmation that models to first
order capture the behavior of the physical climate system
and lends credence to applying the models to projecting
future climates.
[4] One curious aspect of this result is that it is also well
known [Houghton et al., 2001] that the same models that
agree in simulating the anomaly in surface air temperature
differ significantly in their predicted climate sensitivity. The
cited range in climate sensitivity from a wide collection of
models is usually 1.5 to 4.5°C for a doubling of CO
2
, where
most global climate models used for climate change studies
vary by at least a factor of two in equilibrium sensitivity.
[5] The question is: if climate models differ by a factor of
2 to 3 in their climate sensitivity, how can they all simulate
the global temperature record with a reasonable degree of
accuracy. Kerr [2007] and S. E. Schwartz et al. (Quantifying
climate change too rosy a picture?, available at www.
nature.com/reports/climatechange, 2007) recently pointed
out the importance of understanding the answer to this
question. Indeed, Kerr [2007] referred to the present work,
and the current paper provides the ‘‘widely circulated
analysis’’ referred to by Kerr [2007]. This report investi-
gates the most probable explanation for such an agreement.
It uses published results from a wide variety of model
simulations to understand this apparent paradox between
model climate responses for the 20th century, but diverse
climate model sensitivity.
2. Method
[6] The application of simple climate models has eluci-
dated the most important factors that, to first order, deter-
mine Earth’s global mean surface temperature. A number of
studies [Raper et al., 2001; Forest et al., 2002; Knutti et al.,
2002] have shown that there are three fundamental climate
factors, namely: the climate forcing, the climate sensitivity
and the efficiency of ocean heat uptake. Given these three
factors one can calculate the evolution of the global mean
surface temperature. All of the models applied to simulating
the 20th century climate represent these factors in varying
degrees of sophistication. The focus of the present work is
on two of these factors: climate forcing and climate sensi-
tivity. The role of the efficiency of ocean heat uptake will be
discussed later. In the simpler energy balance models these
three factors are specified, while in the more comprehensive
three dimensional climate models the climate sensitivity and
efficiency of ocean heat uptake are predicted.
[7] The climate forcing of the 20th century is calculated
by assuming time evolving growth curves for greenhouse
gas concentrations, aerosol concentrations and natural forc-
ing factors that include solar variability and volcanic aero-
sols. It is important to note that the change in radiative flux
is calculated and not prescribed in the fully coupled climate
models. In the simpler energy balance models the actual
radiative forcing is prescribed. The temporal evolution of
the well-mixed greenhouse gases is more constrained by
GEOPHYSICAL RESEARCH LETTERS, VOL. 34, L22710, doi:10.1029/2007GL031383, 2007
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L22710 1of4
observations compared to changes in tropospheric aerosols
[Houghton et al., 2001]. Given the evolution of these
forcing agents a temporal evolution of climate forcing is
applied to the climate system, which then responds to the
forcing. The magnitude of the surface temperature response
for a given forcing is determined by the climate sensitivity.
Uncertainties in climate forcing will be reflected in uncer-
tainties in a models ability to replicate the observed climate
record.
[8] The climate sensitivity is determined by a myriad of
feedback processes in the climate system, which includes
water vapor, clouds, sea ice and other processes. It is
believed that much of the range in model climate sensitivity
is due to uncertainties in cloud feedback processes [Cess et
al., 1996]. The reason for the 2 to 3 fold spread in climate
sensitivity has been of great concern to the climate com-
munity [Kerr, 2004]. Although much focus has been on
uncertainties in climate sensitivity, the question arises as to
how important are uncertainties in forcing and the implica-
tions of these uncertainties in the ability to simulate the
climate of the 20th century [Hansen and Sato, 2001].
[9] A large number of climate modeling groups have
carried out simulations of the 20th century. These simula-
tions employed a number of forcing agents in the simula-
tions. Although there are established data for the time
evolution of well-mixed greenhouse gases, there are no
established standard datasets for ozone, aerosols or natural
forcing factors. Results from nine fully coupled climate
models [Dai et al., 2001; Boer et al., 2000; Roeckner et al.,
1999; Haywood et al., 1997; Mitchell et al., 1995; Tett et al.,
2002; Meehl et al., 2004; Meehl et al., 2000] and two
energy balance models [Crowley and Kim, 1999;
Andronova and Schlesinger, 2000] have been used to
consider the relationship between total anthropogenic cli-
mate forcing and climate sensitivity. All of these simula-
tions show very good agreement between the simulated
anomaly in global mean surface temperature and the obser-
vational record. Many of these studies document the models
equilibrium climate sensitivity and the aerosol and total
forcing over the 20th century time period.
[10] The total climate forcings used in the present anal-
ysis were taken from the above cited references. When only
total climate forcings were available from the studies, the
total greenhouse forcing was used from Houghton et al.
[2001] to back out the net aerosol forcing. Since the
uncertainty in total greenhouse forcing (20% or less) is
much smaller than that due to aerosols, this approach
introduces only small uncertainty in the present analysis.
3. Results
[11] The theoretical relationship between climate forcing
and climate sensitivity is obtained by considering Earth’s
global energy budget [e.g., Andreae et al., 2005],
DQ¼lDTþH;ð1Þ
which states that the forcing of the climate system, DQ, is
balanced by energy escaping to space, lDT, and energy
stored in the oceans, H. Note that the total forcing of the
system, DQ, is defined as the change in total radiative
forcing between the end of the 20th century and the time
period of the late 1800s. lis the climate feedback parameter
and is determined by the various feedback processes in the
system. The climate sensitivity, DT
2X
, is defined as the
change in equilibrium global surface-air temperature due to
a doubling of carbon dioxide, where at equilibrium, H = 0,
and (1) implies,
DQ2X ¼lDT2X:ð2Þ
Using (2), l=DQ
2X
/DT
2X
, which means (1) can be written
as,
DQ¼DTDQ2X
ðÞ=DT2X þH:ð3Þ
The forcing due to a doubling of carbon dioxide is
3.7 Wm
2
[Andreae et al., 2005], while the observed
change in surface-air temperature is taken to be 0.6°C. The
change in ocean energy storage is 0.7 Wm
2
[Wigley, 2005].
Substituting these values into (3) yields,
DQ¼2:22=DT2X þ0:7ð4Þ
This expression indicates an inverse relationship between
total forcing and climate sensitivity. With regards to the
change in ocean heat storage, Hansen et al. [2005] estimate
an uncertainty in H of ±0.15 Wm
2
. An analysis of coupled
model simulations forced with a 1% per year increase in
carbon dioxide indicates a spread in ocean energy storage,
at the point of doubling, of 0.4 Wm
2
. Based on these
estimate, the present analysis will assume an uncertainty of
±0.2 Wm
2
in H.
[12] The model results for total anthropogenic forcing,
DQ, and equilibrium climate sensitivity, DT
2X
, are shown
in Figure 1, while the solid line is based on (4), and the
dashed lines above and below this central line arise from the
±0.2 Wm
2
uncertainty in H. It is assumed that the natural
forcing is much smaller than the anthropogenic forcing.
These results clearly illustrate a strong inverse correlation
between total anthropogenic forcing used for the 20th
century and the model’s climate sensitivity. Indicating that
models with low climate sensitivity require a relatively
higher total anthropogenic forcing than models with higher
climate sensitivity.
[13] It may be argued that it would be more accurate to
use a measure of the transient climate sensitivity in this
analysis, since the simulation of the 20th century is a
transient phenomenon. However, the transient climate re-
sponse as defined as the change in global mean surface air
temperature at the time of doubling in models assuming 1%
per year increase in CO
2
show a similar range as the
equilibrium sensitivity (1.4 to 3.8°C, see Table 9.1 by
Houghton et al. [2001]). So whether equilibrium or transient
sensitivity is used the results in Figure 1 will be unchanged.
[14] Note that the range in total anthropogenic forcing is
slightly over a factor of 2, which is the same order as the
uncertainty in climate sensitivity. These results explain to a
large degree why models with such diverse climate sensi-
tivities can all simulate the global anomaly in surface
temperature. The magnitude of applied anthropogenic total
forcing compensates for the model sensitivity.
[15] Although there is a clear inverse correlation between
the forcing and the climate sensitivity there is some spread
in the data points. Note that all the model results, except for
one, fall close to or within the theoretical curves based on
L22710 KIEHL: CLIMATE MODEL RESPONSE AND SENSITIVITY L22710
2of4
the estimated uncertainty in H. This strongly suggests that
the scatter among the models is mostly due to the range in
modeled change in ocean heat storage.
[16] What is the major reason for the large uncertainty in
total anthropogenic forcing? Figure 2 shows the correlation
between total anthropogenic forcing and forcing due to
tropospheric aerosols. There is a strong positive correlation
between these two quantities with a near 3-fold range in the
magnitude of aerosol forcing applied over the 20th century.
This large uncertainty in aerosol forcing has recently been
noted [Anderson et al., 2003; Schwartz, 2004] as a signif-
icant challenge to the climate modeling community. Thus,
the large uncertainty in aerosols over the past leads to a
wide range in total anthropogenic forcing. Some of the
models used in these simulations employed only the direct
effect, while others used both direct and indirect effects of
aerosols, which makes a more detailed comparison of
simulated aerosol forcing difficult.
4. Conclusions
[17] These results indicate that the range of uncertainty in
anthropogenic forcing of the past century is as large as the
uncertainty in climate sensitivity and that much of forcing
uncertainty is due to aerosols. In many models aerosol
forcing is not applied as an external forcing, but is calcu-
lated as an integral component of the system. Many current
models predict aerosol concentrations interactively within
the climate model and this concentration is then used to
predict the direct and indirect forcing effects on the climate
system. Thus, it may be difficult to arrive at a standard
approach that all models could employ for use in compar-
ison of simulations forced in the same manner. However, a
first step would be for models to employ standard emissions
for aerosol gas precursors and particulate emissions.
[18] It is important to note that in spite of the threefold
uncertainty in aerosol forcing, all of the models do predict a
warming of the climate system over the later part of the 20th
century. The warming is in essence bounded by the fact that
climate sensitivity is a positive quantity and the total
forcings used by modelers are also positive. This implies
that the total forcing of the 20th century cannot be negative,
i.e. the negative aerosol forcing cannot be larger than the
positive greenhouse forcing, which bounds the magnitude
of the total aerosol forcing.
[19] It could also be argued that these results do not
invalidate the application of climate models to projecting
future climate for, at least, two reasons. First, within the
range of uncertainty in aerosol forcing models have been
benchmarked against the 20th century as a way of establish-
ing a reasonable initial state for future predictions. The
analogy would be to weather forecasting where models
assimilate information to constrain the present state for
improved prediction purposes. Climate models are forced
within a range of uncertainty and yield a reasonable present
state, which improves the models predictive capabilities.
Second, many of the emission scenarios for the next 50 to
100 years indicate a substantial increase in greenhouse
gases with associated large increase in greenhouse forcing.
Given that the lifetime of these gases is orders of magnitude
larger than that of aerosols, future anthropogenic forcing is
dominated by greenhouse gases. Thus, the relative uncer-
tainty in aerosol forcing may be less important for projec-
ting future climate change.
Figure 1. Total Anthropogenic Forcing (Wm
2
) versus
equilibrium climate sensitivity (°C) from nine coupled
climate models and two energy balance models that were
used to simulate the climate of the 20th century. Solid line is
theoretical relationship from equation (4). Dashed lines arise
from assuming a ±0.2 Wm
2
uncertainty in ocean energy
storage in equation (4).
Figure 2. Total anthropogenic forcing (Wm
2
) versus
aerosol forcing (Wm
2
) from nine fully coupled climate
models and two energy balance models used to simulate the
20th century.
L22710 KIEHL: CLIMATE MODEL RESPONSE AND SENSITIVITY L22710
3of4
[20] Finally, the focus of this study has been on anthro-
pogenic forcing. There is also a range of uncertainty in
natural forcing factors such as solar irradiance and volcanic
aerosol amount. It would of value to reduce uncertainties in
these forcing factors as well. It would also be of great value
to investigate the robustness of these results relative to the
latest versions of coupled climate system models. However,
given the fundamental physical relationship among climate
response, climate forcing and sensitivity, i.e. (3), it is hard to
imagine that these results do not apply to the latest coupled
models.
[21]Acknowledgments. The National Center for Atmospheric Re-
search is sponsored by the National Science Foundation. This work was
supported in part by the Department of Energy Office of Science Climate
Change Prediction Program.
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Many CMIP6 models exhibit a substantial cold bias in global mean surface temperature (GMST) in the latter part of the 20th century. An overly strong negative aerosol forcing has been suggested as a leading contributor to this bias. An updated configuration of UKESM1, UKESM1.1, has been developed with the aim of reducing the historical cold bias in this model. Changes implemented include an improved representation of SO2 dry deposition along with several other smaller modifications to the aerosol scheme and a retuning of some uncertain parameters of the fully coupled Earth System Model. The Diagnostic, Evaluation and Characterization of Klima (DECK) experiments, a 6-member historical ensemble and a subset of future scenario simulations are completed. In addition, the total anthropogenic effective radiative forcing (ERF), its components and the effective and transient climate sensitivities are also computed. The UKESM1.1 pre-industrial climate is warmer than UKESM1 by up to 0.75 K and a significant improvement in the historical GMST record is simulated with the magnitude of the cold bias reduced by over 50 %. The warmer climate increases ocean heat uptake in the northern hemisphere oceans and reduces Arctic sea ice in better agreement with observations. Changes to the aerosol and related cloud properties are the key drivers of the improved GMST simulation despite only a modest change in aerosol ERF (+0.08 Wm-2). The total anthropogenic ERF increases from 1.76 Wm-2 in UKESM1 to 1.84 Wm-2 in UKESM1.1. The effective climate sensitivity (5.27 K) and transient climate response (2.64 K) remain largely unchanged from UKESM1 (5.36 K and 2.76 K respectively).
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This study focuses on methods to estimate dry marine aerosol surface area (SA) from bulk optical measurements. Aerosol SA is used in many models' ice nucleating particle (INP) parameterizations, as well as influencing particle light scattering, hygroscopic growth, and reactivity, but direct observations are scarce in the Southern Ocean (SO). Two campaigns jointly conducted in austral summer 2018 provided co‐located measurements of aerosol SA from particle size distributions and lidar to evaluate SA estimation methods in this region. Mie theory calculations based on measured size distributions were used to test a proposed approximation for dry aerosol SA, which relies on estimating effective scattering efficiency (Q) as a function of Ångström exponent (å). For distributions with dry å < 1, Q = 2 was found to be a good approximation within ±50%, but for distributions with dry å > 1, an assumption of Q = 3 as in some prior studies underestimates dry aerosol SA by a factor of 2 or more. We propose a new relationship between dry å and Q, which can be used for −0.2 < å < 2, and suggest å = 0.8 as the cutoff between primary and secondary marine aerosol‐dominated distributions. Application of a published methodology to retrieve dry marine aerosol SA from lidar extinction profiles overestimated aerosol SA by a factor of 3–5 during these campaigns. Using Microtops aerosol optical thickness measurements, we derive alternative lidar conversion parameters from our observations, applicable to marine aerosol over the SO.
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Climate change is leading to changing patterns of precipitation and increasingly extreme global weather. There is an urgent need to synthesize our current knowledge on climate risks to water security, which in turn is fundamental for achieving sustainable water management. Climate Risk and Sustainable Water Management discusses hydrological extremes, climate variability, climate impact assessment, risk analysis, and hydrological modelling. It provides a comprehensive interdisciplinary exploration of climate risks to water security, helping to guide sustainable water management in a changing and uncertain future. The relevant theory is accessibly explained using examples throughout, helping readers to apply the knowledge learned to their own situations and challenges. This textbook is especially valuable to students of hydrology, resource management, climate change, and geography, as well as a reference textbook for researchers, civil and environmental engineers, and water management professionals concerned with water-related hazards, water cycles, and climate change.
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Aerosol particles affect Earth's climate through processes of scattering and absorption of radiation in the atmosphere, through interaction with clouds, and by altering the albedo of snow and ice. This chapter describes how these processes affect Earth's energy balance and how changes in energy balance affect temperature and precipitation. Following a short history of our understanding of aerosol effects on climate, the chapter defines the energy flows within the climate system and the ways in which aerosol affects these flows. It then defines the concept of radiative forcing of climate and summarizes current estimates of the magnitude of aerosol radiative forcing over the industrial period. The chapter concludes by describing the response of Earth's temperature and precipitation to radiative perturbations in terms of climate sensitivity and hydrological sensitivity.
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Four global coupled climate models with different combinations of atmosphere, ocean, land surface, and sea ice components are compared in idealized forcing (1% CO2 increase) experiments. The four models are the Climate System Model (CSM), the Parallel Climate Model (PCM), the PCM/CSM Transition Model (PCTM), and the Community Climate System Model (CCSM). The hypothesis is posed that models with similar atmospheric model components should show a similar globally averaged dynamically coupled response to increasing CO2 in spite of different ocean, sea ice, and land formulations. Conversely, models with different atmospheric components should be most different in terms of the coupled globally averaged response. The two models with the same atmosphere and sea ice but different ocean components (PCM and PCTM) have the most similar response to increasing CO2, followed closely by CSM with comparable atmosphere and different ocean and sea ice from either PCM or PCTM. The fourth model, CCSM, has a different response from the other three and, in particular, is different from PCTM in spite of having the same ocean and sea ice but different atmospheric model component. These results support the hypothesis that, to a greater degree than the other components, the atmospheric model ``manages'' the relevant global feedbacks including sea ice albedo, water vapor, and clouds. The atmospheric model also affects the meridional overturning circulation in the ocean, as well as the ocean heat uptake characteristics. This is due to changes in surface fluxes of heat and freshwater that affect surface density in the ocean. For global sensitivity measures, the ocean, sea ice, and land surface play secondary roles, even though differences in these components can be important for regional climate changes.
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Using a coupled atmosphere/ocean general circulation model, we have simulated the climatic response to natural and anthropogenic forcings from 1860 to 1997. The model, HadCM3, requires no flux adjustment and has an interactive sulphur cycle, a simple parameterization of the effect of aerosols on cloud albedo (first indirect effect), and a radiation scheme that allows explicit representation of well-mixed greenhouse gases. Simulations were carried out in which the model was forced with changes in natural forcings (solar irradiance and stratospheric aerosol due to explosive volcanic eruptions), well-mixed greenhouse gases alone, tropospheric anthropogenic forcings (tropospheric ozone, well-mixed greenhouse gases, and the direct and first indirect effects of sulphate aerosol), and anthropogenic forcings (tropospheric anthropogenic forcings and stratospheric ozone decline). Using an ``optimal detection'' methodology to examine temperature changes near the surface and throughout the free atmosphere, we find that we can detect the effects of changes in well-mixed greenhouse gases, other anthropogenic forcings (mainly the effects of sulphate aerosols on cloud albedo), and natural forcings. Thus these have all had a significant impact on temperature. We estimate the linear trend in global mean near-surface temperature from well-mixed greenhouse gases to be 0.9 +/- 0.24 K/century, offset by cooling from other anthropogenic forcings of 0.4 +/- 0.26 K/century, giving a total anthropogenic warming trend of 0.5 +/- 0.15 K/century. Over the entire century, natural forcings give a linear trend close to zero. We found no evidence that simulated changes in near-surface temperature due to anthropogenic forcings were in error. However, the simulated tropospheric response, since the 1960s, is ~50% too large. Our analysis suggests that the early twentieth century warming can best be explained by a combination of warming due to increases in greenhouse gases and natural forcing, some cooling due to other anthropogenic forcings, and a substantial, but not implausible, contribution from internal variability. In the second half of the century we find that the warming is largely caused by changes in greenhouse gases, with changes in sulphates and, perhaps, volcanic aerosol offsetting approximately one third of the warming. Warming in the troposphere, since the 1960s, is probably mainly due to anthropogenic forcings, with a negligible contribution from natural forcings.
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This study investigates changes in surface air temperature (SAT), hydrology and the thermohaline circulation due to the the radiative forcing of anthropogenic greenhouse gases and the direct radiative forcing (DRF) of sulfate aerosols in the GFDL coupled ocean-atmosphere model. Three 300-year model integrations are performed with increasing greenhouse gas concentrations only, increasing sulfate aerosol concentrations only and increasing greenhouse gas and sulfate aerosol concentrations. A control integration is also performed keeping concentrations of sulfate and carbon dioxide fixed. The global annual mean SAT change when both greenhouse gases and sulfate aerosols are included is in better agreement with observations than when greenhouse gases alone are included. When the global annual mean SAT change from a model integration that includes only increases in greenhouse gases is added to that from a model integration that includes only increases in sulfate, the resulting global SAT change is approximately equal to that from a model integration that includes increases in both greenhouse gases and sulfate aerosol throughout the integration period. Similar results are found for global annual mean precipitation changes and for the geographical distribution of both SAT and precipitation changes indicating that the climate response is linearly additive for the two types of forcing considered here. Changes in the mid-continental summer dryness and thermohaline circulation are also briefly discussed.
Article
During the past two decades there has been considerable discussion about the relative contribution of different factors to the temperature changes observed now over the past 142 years. Among these factors are the “external’ factors of human (anthropogenic) activity, volcanoes and putative variations in the irradiance of the sun, and the “internal” factor of natural variability. Here, by using a simple climate/ocean model to simulate the observed temperature changes for different state-of-the-art radiative-forcing models, we present strong evidence that while the anthropogenic effect has steadily increased in size during the entire 20th century such that it presently is the dominant external forcing of the climate system, there is a residual factor at work within the climate system, whether a natural oscillation or something else as yet unknown. This has an important implication for our expectation of future temperature changes.
Article
Development of improved proxy estimates of climate forcing and temperature change over the past six centuries provides a new opportunity to examine the role of forced variability in the climate system. We utilize an energy balance model to estimate that as much as 18-34% of low frequency temperature change over the preanthropogenic interval could be forced by volcanism and solar variability. Comparison of residuals with estimates of unforced variability from control runs of coupled models indicates that the spectra of the two time series agree at the 90% significance level.
Article
ABSTRACT The Climate System Model, a coupled global climate model without ‘‘flux adjustments’’ recently developed at the National Center for Atmospheric Research, was used to simulate the twentieth-century climate using historical greenhouse,gas and sulfate aerosol forcing. This simulation was,extended,through the twenty-first century under two newly developed scenarios, a business-as-usual case (ACACIA-BAU, CO2 710 ppmv in 2100) and a CO2 stabilization case (STA550, CO 2 540 ppmv in 2100). Here we compare the simulated and observed twentieth-century climate, and then describe the simulated climates for the twenty-first century. The model,simulates the spatial and temporal,variations of the twentieth-century climate reasonably well. These include the rapid rise in global and zonal mean surface temperatures since the late 1970s, the precipitation increases over northern mid- and high-latitude land areas, ENSO-induced precipitation anomalies, and Pole‐ midlatitude oscillations (such as the North Atlantic oscillation) in sea level pressure fields. The model,has a cold bias (28‐68C) in surface air temperature over land, overestimates of cloudiness (by 10%‐30%) over land, and underestimates,of marine stratus clouds to the west of North and South America and Africa. The projected global surface warming,from the 1990s to the 2090s is ;1.98C under the BAU scenario and ;1.58C under the STA550 scenario. In both cases, the midstratosphere cools due to the increase in CO 2, whereas the lower stratosphere warms in response to recovery of the ozone layer. As in other coupled models, the surface warming,is largest at winter high latitudes ($5.08C from the 1990s to the 2090s) and smallest (;1.08C) over the southern oceans, and is larger over land areas than ocean areas. Globally averaged precipitation increases by ;3.5% (3.0%) from the 1990s to the 2090s in the BAU (STA550) case. In the BAU case, large precipitation increases (up to 50%) occur over northern mid- and high latitudes and over India and the Arabian Peninsula. Marked differences occur between,the BAU and STA550 regional precipitation changes resulting from inter- decadal variability. Surface evaporation increases at all latitudes except for 60 8‐908S. Water vapor from increased tropical evaporation is transported into mid- and high latitudes and returned to the surface through increased precipitation there. Changes in soil moisture content are small (within 63%). Total cloud cover changes little, although there is an upward,shift of midlevel clouds. Surface diurnal temperature range decreases by about 0.28‐ 0.58C over most land areas. The 2‐8-day synoptic storm activity decreases (by up to 10%) at low latitudes and over midlatitude oceans, but increases over Eurasia and Canada. The cores of subtropical jets move slightly up- and equatorward. Associated with reduced latitudinal temperature gradients over mid- and high latitudes, the wintertime Ferrel cell weakens (by 10%‐15%). The Hadley circulation also weakens (by ;10%), partly due to