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Simulation of climate change
Renewabh' Energy Vol. 3, No. 4i5. pp. 4 3 3 4 4 5 , 1993 Printed in Great Britain.
09613 1481/93 $6.00 + . 0 0 Pergamon Press Ltd
SIMULATION OF CLIMATE CHANGE J. F. B. MITCHELL Hadley Centre for Climate Prediction and Research, Meteorological Office, Bracknell RGI2 2SZ, U.K. Abstract The use of climate models to understand and predict climate change is described, using examples fiom numerical studies of the effects of enhanced atmospheric CO,.
I. I N T R O D U C T I O N - - W H Y M O D E L CLIMATE?
2. T H E " G R E E N H O U S E " EFFECT
The increases in atmospheric Greenhouse gases since 1795 have a radiative effect equivalent to a 60% increase in carbon dioxide concentrations, and by early next century, are expected to be equivalent to a doubling of carbon dioxide concentration. Simulations with detailed climate models indicate that this would produce a warming of 2 5 K in global mean surface temperature at equilibrium, with accompanying changes in precipitation, sea level and other parameters. The observed increase of 0.5 K since 1900 is consistent with the lower range of the estimated potential increase, allowing for a possible slowing of the global mean warming due to the ocean's large thermal inertia. Thus, man-made climate change is not just a possibility, it may already be occurring. Consequently, there is an ever pressing need to predict the likely changes in climate due to increases in trace gases in order to guide future energy policies and to minimize the possible climatic impacts. Detailed three-dimensional models of climate are the most promising method of providing the detailed information required for climatic impact assessment. There is also considerable interest as to why the earth's climate has changed in the past. Climate models provide a means of testing theories of climate change. Conversely, periods from which reliable and wide-spread palaeoclimatic data are available may be used as a test of the fidelity of climate models, especially if the factors producing the climatic change arc well known. This paper gives a brief review of work up to the time of the IPCC report (Houghton et al. [1], to which the reader is referred for a more detailed text) and includes references to results obtained since then. Note that examples are taken predominantly from Meteorological Office studies.
The globally averaged radiative heat balance of the earth atmosphere system may be approximated by (S0/4)(1--:0 = r~T~,4
(1)
where So is the solar "constant", 7 is the fraction of solar radiation reflected by the earth and atmosphere, a is Stefan's constant and T,. is the mean or effective radiative temperature of the system. T,. is the radiative equilibrium temperature that the earth's surface would reach if the atmosphere was transparent to longwave (thermal or infrared) radiation. With the current value of ~ (0.3), T,. = 255 K, ( - 18 C) some 33 K below the current observed global mean surface temperature. Now consider a single layer atmosphere, longwave emissivity c and shortwave albedo ~ in radiative equilibrium with the surface (Fig. 1). For convenience, it will be assumed that the atmosphere does not absorb solar radiation. The surface temperature T, is given by T 4 = T~ 4// ( l - e / 2 )
(2)
and the atmospheric temperature T is given by T 4
,]-4 =
}.
(31
Thus, gases which absorb and emit long-wave radiation (greenhouse gases) warm the surface and cool the atmosphere. As an exercise, the reader can show that in a two-level atmosphere in radiative equilibrium, temperature decreases with height. In practice, the troposphere is not generally in radiative equilibrium, but is heated convectively from the surface. The global mean lapse rate, about 6 C/kin, is 433
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J. F. B. MITCHELL
( T ATMOSPHERE Eo-T4 T. SURFACE Fig. l. In an idealized single layer atmosphere, reflectivity ~, long wave emissivity e and temperature T in radiative equilibrium with the surface at temperature T,.
slightly less than the dry adiabatic lapse rate due to latent heat released in regions of saturated ascent. The radiative equilibrium temperature of - 1 8 " C corresponds to a height of 5.5 km (point a on the solid profile in Fig. 2). An increase in the concentration of greenhouse gases raises the effective emitting level, (point b in Fig. 2) and reduces the effective emitting temperature Tc and outgoing radiance a t e . The system warms until the temperature at the new emitting level rises to the original value T~ (point c). The stratosphere will cool if the concentration of greenhouse gases there is increased. The stratosphere is not convectively coupled to the surface but is in radiative equilibrium; an increase in long wave absorbers will produce enhanced emission to space which at equilibrium is compensated by a fall in emitting temperature. 3. THE PRINCIPAL ABSORBERS, PAST, PRESENT AND FUTURE
The concentration and radiative characteristics of the climatically most important long-wave absorbers
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in the contemporary atmosphere are listed in Table 1, based on Dickinson and Cicerone [2] and Ramanathan et al. [3]. The greenhouse heating is defined as the change in net downward flux at the tropopause due to the presence of each gas. Since increasing the concentration of greenhouse gases produces a slight increase in the downward flux from the stratosphere, the change in net flux at the tropopause rather than at the top of the atmosphere is considered [9]. Note that the troposphere and surface are strongly coupled and hence can be regarded as a single system. Water vapour is by far the most important Greenhouse gas, followed by carbon dioxide. Although the concentrations of chlorofluorocarbons (CFCs) C F C l l and CFC12 are 10 6 that of carbon dioxide, their contribution to radiative heating is only a factor 103 less. These gases have absorption bands which are both very strong and lie in the atmospheric "window" from about 833 cm ~ to 1250 cm ~, where there is little absorption by other gases. Also shown in Table 1 are estimates of the atmospheric lifetimes--note the long lifetimes of CFCs. Estimates of pre-industrial (1795) concentrations of the main trace gases (other than water vapour) are shown in Table 2. The concentrations of carbon dioxide, methane and nitrous oxide are deduced from ice-core sampling. CFCs are produced solely by industrial activity so their pre-industrial concentration is zero. Gases other than CO_, produce over 30% of the radiative perturbation to date, and the total effect already exceeds that due to doubling carbon dioxide concentrations. Estimates of the concentrations of gases in 2025 based on the IPCC "Business-as-usual" scenario are given in Table 2, along with the increase in greenhouse forcing. There is considerable uncertainty in these estimates the first three gases in Table 2 undergo natural cycles which are not completely understood, and for all gases, the industrial contribution is dependent on the world economy and the effectiveness of recent agreements to limit production such as those for CFCs. If the estimates in Table 2 are not greatly in error, the radiative effect of the increases in all gases since the industrial revolution to 2025 will be equivalent to a doubling of CO,. Note the contribution from HCFCs, which have a similar radiative effect to CFCs, but a much shorter lifetime (typically 15 years). The effect of alternative scenarios can be estimated from Table 2 by noting that the radiative effect of carbon dioxide varies approximately logarithmically with concentration [6] and that of methane and nitrous oxide as the square root of their concentration. The effect of C F C I I and CFC12 vary linearly with
Simulation of climate change
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Table 1. Current concentrations and "greenhouse heating" due to trace gases. The main absorption bands and band strengths (a measure of the probability of a molecule absorbing a photon at the band wavelength) are shown for the less abundant gases and, where appropriate, an estimate of the atmospheric lifetime Principal absorption bands
Gas
Concentration (ppm)
Water vapour Carbon dioxide Methane Nitrous oxide Ozone CFCI I
-3000 353 1.7 0.30 10 100xl0 3 0.22 x 10 3
10 150
0.38xi0 '
13(t
CFCI2
Lifetime (years)
65
c o n c e n t r a t i o n because of their low c o n c e n t r a t i o n s a n d the fact t h a t they a b s o r b at wavelengths where there is little a b s o r p t i o n by other gases.
4. CLIMATE FEEDBACKS IN C A R B O N DIOXIDE EXPERIMENTS
The radiative p e r t u r b a t i o n due to e n h a n c i n g trace gases can (in principle) be calculated to any desired accuracy. D o u b l i n g c a r b o n dioxide a m o u n t s increases the heating o f the t r o p o p a u s e and surface by 4 W m ~ [7] which, assuming the current climate system behaves as a black body at m e a n t e m p e r a t u r e s near 255 K, would produce a w a r m i n g o f 1 . 1 C . However, the a t m o s p h e r i c response to changes in radiative heating is complex involving m a n y processes which are not well understood. These m a y amplify the p e r t u r b a t i o n (positive feedbacks) or d a m p it (negative feedbacks).
Position (cm ~)
Strength cm ~(atmcm) t STP
667 1306 1285 1041 846 1085 915 1095 1152
(many bands) 185 235 376 1965 736 1568 1239 836
Greenhouse heating (W m 2) ~ 100 - 50 1.7 1.3 1.3 0.06 0.12
M o s t equilibrium experiments to determine the climatic effects of increases in trace gases have assumed a d o u b l i n g or q u a d r u p l i n g of c a r b o n dioxide concentrations. The vertical profile of the radiative pert u r b a t i o n due to the o t h e r gases in Table 2 is qualitatively similar to that due to increasing c a r b o n dioxide, (except near the t r o p o p a u s e where the m i n o r gases produce a slight w a r m i n g as opposed to a cooling [3, 8] so experiments with increased c a r b o n dioxide only are p r o b a b l y a d e q u a t e to represent the effect of all the gases, given the m a g n i t u d e of other uncertainties. Here and in the next section, we will consider the equilibrium response to d o u b l i n g c a r b o n dioxide concentrations. First. we consider the main climate feedbacks which have been identified in numerical experiments. A w a r m e r a t m o s p h e r e will hold more water vapour, and hence enhance the radiative p e r t u r b a t i o n due to
Table 2. Past and projected greenhouse gas concentrations and associated changes in "'greenhouse" heating AQ
Gas Carbon dioxide Methane Nitrous oxide CFCI1 CFCI2 Total
Assumed 1860 concentration
AQ 1860 to 1985
Estimated 2035 concentration (ppm)
Estimated AQ 1985 2035 (W m :) range
275 1.1 0.28 0 0
1.3 0.4 0.05 0.06 0.12 1.9
475 2.8 0.38 1.6x10 3 2.8x10 ~
1.8 0.5 0.15 0.35 0.69 3.5
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J . F . B . MITCHELL
carbon dioxide. Higher temperatures reduce the extent of highly reflective snow and ice, and so increase the absorption of solar radiation. In most simulations with increased carbon dioxide, cloud amount decreases, reducing the amount of insolation reflected back to space, and the mean cloud height increases, further enhancing the greenhouse effect. It is also likely that cloud radiative properties may change. An increase in atmospheric moisture would tend to increase cloud water content and hence the reflectivity of cloud, producing a negative feedback. Thick clouds behave as black bodies at infrared wavelengths, but thin high clouds may have an emissivity considerably less than unity. An increase in cloud water would tend to increase the longwave emissivity of high cloud and enhance the greenhouse effect, adding a further positive feedback. The strength of individual feedbacks simulated in GCM experiments has been quantified using a simple zero-dimensional energy balance model dAT C , dt + ; t A T = AQ
(4)
where AQ is the radiative perturbation, AT is the change in surface temperature, C, is the effective heat capacity of the system, and 2 is defined as the feedback parameter. At equilibrium, AT~q = AQ/2. Thus the smaller 2, the greater AT~q, implying a larger positive feedback. Assuming the feedbacks are linear and independent
)t = ~ 2~; 2~ = AQi/AT,.,~
(5)
where i denotes the individual feedbacks, and AQi is the radiative perturbation due to the process i alone. For example, if i denotes changes in water vapour, then AQi is the radiative perturbation due to the increase in water vapour between the perturbed and control simulations, in the absence of changes in other parameters. Typical values for 2i from GCM experiments arc given in Table 3. The water vapour feedback is easily the strongest, and there is good agreement among different models [97] and with observations [I0]. Lindzen [11] argues that "existing climate models have considerable difficulty predicting upper level water vapour", and that the water vapour feedback could even be negative because of drying due to enhanced subsidence accompanying deeper moist convection, but this argument has been widely refuted [12-14] (see also Nature 347, pages 467 and 491). Drying due to enhanced subsidence is evident in isolated regions of the sub tropics in recent Meteorological Office experiments [15], but the net water feedback
Table 3. Analysis of feedbacks and temperature changes due to doubling CO2, based on typical values from GCM experiments Feedback None Water vapour Ice/snow Cloud amount Cloud radiative properties
Strength Temp.change (W m -2 K ~) (cumulative) +3.7 - 1.4 - 0.3 - 0.9 -0.1 0.5
1.1 1.7 2.1 4.0 2.74.5
is strongly positive due to the dominance of other processes). The ice snow albedo feedback simulated by models is small [16], though it should be noted that the representation of sea-ice in current climate models is simplistic. However, even in the case of snow albedo feedback, there is a large variation between the response in different models [17]. Small changes in the amount and radiative properties of clouds can have a large effect on the net heating of our planet [18]. It has even been suggested that a strong negative feedback due to cirrus clouds limits the maximum tropical sea surface temperature in the present climate [19]. Thus, one might expect changes in cloud amounts and radiative properties to produce strong climate feedbacks. Mitchell et al. [20] found that the simulated equilibrium global mean temperature change on doubling CO2 varied from 5.2-1.9'C depending on the cloud prediction scheme employed in their model. Even with the same cloud prediction scheme, different models produce a wide range of climate sensitivities [9], indicating the importance of other aspects of the hydrological cycle which affect cloud, and hence which must be represented accurately. The represenation of cloud and associated processes is the major source of uncertainty in the simulation of climate change due to increases in greenhouse gases. Other feedbacks have been analysed using onedimensional radiative~convective models [21]. However, the reader is warned that the different modelling groups estimate the feedbacks in their experiments in different ways [16]. The main value of feedback analysis is in identifying the proceses which most affect climate sensitivity, and in helping to identify the reasons for discrepancies between models. 5. MECHANISMS OF CLIMATE CHANGE The previous section considered some of the main processes governing global mean climate. In this
Simulation of climate change section, we consider some of the mechanisms which lead to geographical and seasonal variations of climate change, using simulations of the equilibrium response to doubling atmospheric carbon dioxide concentrations as an example. A fuller account is given in Section 5 of the IPCC report [22]. The increases in carbon dioxide and other trace gases have been occurring on time-scales of decades to centuries. It is generally assumed that one can ignore changes in the continental ice sheets on this time scale, but not changes in the ocean or sea-ice. Coupled ocean-atmosphere models have until recently been prohibitively expensive to run to equilibrium, so over the last decade atmospheric models coupled to a simple oceanic mixed layer of prescribed depth have been used to model the effects of increased CO_~. In order to allow for the advection of heat by the oceans, some models have included a prescribed oceanic heat flux C such that the mixed layer temperature Tis given by dT ph(7~ dt = S + C
(6)
where p, h and Cp are, respectively, the density, depth and specific heat of the well mixed layer and S is the net downward heat flux from the atmosphere. C may
437
be derived by prescribing the sea (surface) temperature, T t¥om climatology in the atmospheric model and integrating through several annual cycles to determine S as a function of time of year and location. Knowing S, h and dT/dt, one can derive C as a function of time and space, and prescribe it in eq. (6) to determine the evolution of T in the coupled atmosphere mixed layer model. Increasing carbon dioxide concentrations leads to a warming of the troposphere and a cooling of the stratosphere (Fig. 3). In the tropics, the tropospheric warming increases with height, since in low latitudes the lapse rate adjusts towards the moist adiabatic which decreases with increasing temperature. The increase in warming with height is more pronounced in models with penetrative convection schemes as opposed to those with moist convective adjustment. Penetrative schemes are more efficient in transporting moisture upwards, and hence in wanning upper levels [23]. In high latitudes in winter, the low-level inversion confines the warming near the surface. The reduction of snow and sea-ice leads to considerable enhancement of the warming in high latitudes in the winter hemisphere. Note that the remowd of sca-ice in sum-
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met leads to increased absorption of solar radiation and storage of heat in the mixed layer, delaying the onset of freezing in autumn and early winter [16, 24]. This leads to a pronounced warming, or more precisely, a reduced cooling relative to the control. In contrast, over sea-ice in summer, temperatures generally rise to the melting point of ice and are maintained there in both the control and anomaly simulation. Even where sea-ice is temporally removed in summer, the thermal inertia of the oceanic mixed layer substantially reduces the magnitude of the warming. The influence of sea-ice is seen more clearly in the geographical distributions of seasonal mean changes in surface temperature (Fig. 4). During December to February the maximum warming occurs in the Arctic, Hudson Bay and near Kamchatka where sea-ice is thinner or removed altogether in the 2 x CO2 simulation, and the minimum occurs over Antarctic sea-ice in the Ross and Weddell Seas. In models in which seaice extents are excessive in the simulation of present day climate, the high latitude warming is exaggerated and the latitude of the maximum warming may be displaced equatorwards. The warming is generally less over the ocean than over land. Over land, evaporation may be limited by the dryness of the surface so that a greater proportion of the increase in radiative heating is used to raise surface temperature as opposed to increasing evaporation. In middle latitudes in winter, removal of snow in the 2 x C O 2 simulation also enhances the surface warming. The warming is a minimum over the tropical oceans. The saturation vapour pressure for water increases exponentially with temperature, so assuming the relative humidity is approximatly constant, potential evaporation also increases non-linearly with temperature. As a result more of the increase in radiative heating of the surface is converted to latent heat and less to raising surface temperatures and sensible heat as one goes from cold to warm regions. Increased evaporative cooling at the surface is linked to increased warming due to latent heat aloft, consistent with the reduction in lapse rate in the tropics noted above. Changes in cloud are qualitively similar from model to model [25]. In general, there is an increase in high cloud and a reduction in upper and middle and tropospheric cloud which is most pronounced in the tropics and mid-latitudes. This is due to an upward shift of the tropopause and the maximum in cloud in the upper troposphere [26, 27]. The changes in low cloud vary considerably from model to model, though increases in low cloud are generally restricted to middle and high latitudes. Thus in low latitudes, where insolation is greatest, there is a reduction in
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planetary albedo (high cloud is generally assigned a low albedo) leading to enhanced absorption of solar radiation, and in the extratropics, there are substantial increases in high cloud tending to reduce longwave cooling to space. On changing from a cloud prediction scheme based on relative humidity to one based on cloud water, Mitchell et al. [20] found large increases in low cloud in the extratropics, due to ice cloud being replaced by water cloud with a longer lifetime. This weakened the solar feedback, and reduced the equilibrium warming from 5.2 to 2.7 K. The warming of the atmosphere is accompanied by an increase in specific humidity (typically 6 % / C warming, which corresponds to relative humidity remaining almost constant) and in evaporation and precipitation (typically about 3 % / C warming). Precipitation does not increase everywhere, and the spatial scale of the change is smaller than for temperature. Whereas there is substantial agreement between the temperature changes simulated by different models, there is little agreement between the regional details of the changes in precipitation, especially in the tropics. All models produce increased precipitation in high latitudes, particularly in winter. The increase in water vapour produces an increase in the transport of moisture into high latitudes, giving enhanced moisture convergence and precipitation. Most models simulate areas of decreased precipitation outside the intertropical convergence zone (ITCZ) and the subtropics,
Simulation of climate change
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Fig. 6. Changes in global mean temperature assuming IPCC Scenario A "Business-as-usual") simulated using a simple climate model. The low, medium and high estimates correspond to assuming equilibrium sensitivities of 1.5, 2.5 and 4.5' C, respectively, to doubling CO2. (From Houghton et al. [l].)
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Fig. 8. Changes in radiative forcing due to various factors on a 50 year time scale. The policy scenarios are [k)r 2006 2050, ranging from "'business-as-usual'" on the left-hand side to IPCC scenario D, involving draconian reductions in emissions. (From Shine el aL [5].) but there is little spatial correlation from model to model. In general, precipitation in the I T C Z is enhanced. Changes in the variability as well as the mean climate are important in the assessment of the impacts of climatic change. Wilson and Mitchell [28] investigated changes in the variability over Western Europe in a 4 x C O , sensitivity experiment. They found, for example, statistically significant reductions in the frequency and intensity of summer precipitation over Southern Italy (Fig. 5). Most simulations indicate that doubling atmospheric CO_, may reduce the moisture content of the soil in summer in northern mid-latitudes [22]. This is due to stronger long wave heating producing enhanced drying of the surface, especially in
Spring and earlier Summer and, in high latitudes, earlier snowmelt and associated runoff. In some models, the soil moisture content may be further diminished due to reductions in cloud giving stronger solar heating at the surface, or to decrease in summer precipitation [29]. Mitchell and Warrilow [30] found that the "summer drying" in the more northerly latitudes could be reversed if simulated snowmelt over frozen ground was lost as runoff, rather than contributing to the local soil moisture content, indicating that the details of the changes are sensitive to the land surface parametrization used.
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J . F . B . MITCHELL
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6. M O D E L L I N G T H E T R A N S I E N T R E S P O N S E TO I N C R E A S E S IN TRACE GASES
Although the concentration of greenhouse gases has and will continue to increase gradually, the temperature response of the atmosphere is likely to be slowed down by the large thermal inertia of the ocean. If the oceans are assumed to have a constant heat capacity C, [eq. (4)], then the evolution of the temperature change AT due to an instantaneous increase in heating AQ at t = 0 is given by AT = A ? (1 - exp ( - At~C,)). z
(7)
The time T taken to reach ( l - l / e ) of the equilibrium response is C,/2. Assuming 2 = 1 W m 2 K - i and that the warming is mixed uniformly through the deep ocean, v is about 500 years. On the other hand, if the warming is confined to the observed seasonal ocean mixed layer which as a depth of order 100 m, then z is of order 10 years. These two estimates are probably upper and lower limits, respectively, and the actual time scale for the oceans depends on the efficiency with which heat is mixed into the deep ocean and so varies between different parts of the ocean. Manabe et al. [31] have compared the equilibrium response to doubling atmospheric CO2 simulated using a mixed layer ocean with the transient response due to a gradual doubling of CO2 over 70 years using the same model, but the deep ocean included. The inertia of the ocean is such that the globally averaged transient warming is about 70% of the equilibrium warming. However, around the southern circumpolar ocean and the northern north Atlantic, the transient response falls below 40% of the equilibrium response. In these regions, the ocean circulation mixes heat absorbed at the surface through the depth of the ocean, slowing up the rate of warming. Qualitatively similar results have been found using other models (at the Max Planck Institute [32] and the Hadley Centre). Manabe et al. [31] note that apart from western Europe and the southern oceans, the patterns of change are similar to that found in their equilibrium experiment, and remain so through the 100 years of the experiment. The rate of warming will depend on the climate sensitivity 2 [see eq. (7)]. This is illustrated by considering the response of a simple climate model to the increases in greenhouse gases prescribed in IPCC Scenario A [l] which gives an effective doubling of CO2 by 2020 and a quadrupling by 2070. For equilibrium sensitive to doubling CO2 of 1.5, 2.5 and 4.5~'C, the projected rates of warming are 0.2, 0.3 and 0 . 5 C per decade, respectively (Fig. 6).
7. U N C E R T A I N T I E S IN THE S I M U L A T I O N A N D DETECTION OF T H E CLIMATIC EFFECT OF INCREASES IN TRACE GASES
(a) There are uncertainties in the pre-industrial concentration of carbon dioxide, and hence in the change in radiative forcing since then. (b) The size of the equilibrium response to a given increase in gases is known only within a factor of 2 or so (Table 3), due mainly to uncertainties in the modelling of cloud and cloud radiative properties. These problems are currently an area of intensive research. The nature of the regional response, particularly in the hydrological cycle, varies from model to model. These discrepancies may be be reduced by using higher horizontal resolution and improved physical parametrizations. (c) There is much to learn concerning the vertical mixing of heat in the oceans and its representation in numerical models. It is not known whether or not one has to resolve oceanic eddies in order to produce a reliable simulation of the changes in oceanic heat transport. Current global ocean GCMs have a horizontal resolution of 300 500 km. These require large horizontal diffusion coefficients maintain numerical stability but also smooth out the more intense ocean currents. (d) The climatic effects of enhanced trace gas concentrations have to be detected against the background of the natural variability of the atmosphere and ocean. The instrumental temperature record exhibits variability on time scales up to several decades. Some indication of the inherent variability of climate on the decadal time scales may be obtained from long (of order 100 years) simulations of coupled ocean atmosphere models (for example, Fig. 7). This natural variability may have enhanced or reduced any warming due to greenhouse gases. (e) There remains the possibility that other factors are masking (or enhancing) the effects of increases in greenhouse gases. There has been much speculation concerning the possibility of changes in the solar "constant". Accurate measurements of the solar constant have been available only for the last decade or so, and these indicate a decrease of less than 0.1% between 1980 and 1986 [33]. (The climatic effect of a 2% increase in solar constant is thought to be approximately equivalent to that due to doubling carbon dioxide concentrations--[34]). This short time variability is associated with the 11 year sunspot cycle, and assuming that the relationship between the measured variations and sunspot number holds for various sunspot cycles, the variations in solar intensity due to this mechanism has always been less than 0.1% on a
Simulation of climate change decadal timescale. There may be variations on a longer time-scale [35, 36] but the evidence is largely speculative and unquantifled. Evaluations of the impact of solar variability on recent climate are given by Shine el al. [5], Hansen and Laicis [34] and Kelly and Wigley [38], who all conclude that the effects are probably small relative to those of increases in trace gases (Fig. 8). Variations in the concentration and composition of stratospheric aerosol resulting from volcanic eruptions have also been cited as a cause of climatic change, but the indices used to categorize volcanic dust do not allow a good quantitative estimate of the associated radiative effects. Estimates of the radiative cooling due to man-made aerosols [37] suggest that their effect is small relative to that of increases in greenhouse gases. Wigley [39] has pursued speculation that increases in sulphate aerosol from fossil fuel emissions would tend to cool climate, both through their direct radiative effect, and through increasing the reflectivity of cloud by acting as cloud condensation nucleii [40]. However, uncertainties in the concentrations of man-made sulphate aerosols and a lack of quantifiable relationship between aerosol concentration and cloud albedo are such that the possibility of significant climatic effects remain speculative. 8. SIMULATION OF PAST CLIMATE In order to try and limit some of the uncertainties discussed in the previous section, attempts have been made to model past climates and compare the simulated changes with the changes from the present deduced fi'om palaeoclimatic data. Models have also been used to help understand past climates [41]. The two periods chosen most frequently are the last glacial maximum (18 Kbp, i.e. 18,000 years before present) and part of the Holocene around 9 Kbp. During the latter period, perihelion almost coincided with the summer as opposed to the winter solstice, enhancing insolation during the northern summer, especially in high northern latitudes. Here, a brief summary of some recent simulations for 9 Kbp [42, 43], will be given. This period is of interest because of the following reasons. (a) The changes in boundary conditions are simple : the changes in orbital parameters are well known, C O , concentrations are believed to have been similar to present, and the ice sheet over North America was relatively small in extent. (b) There is a large amount of palaeoclimatic data available froln that period. In the initial experiment, only the orbital parameters were altered. The enhanced insolation during
443
the boreal summer produces an increase in surface temperature over the northern mid-latitude continents. This enhances the land sea contrast, lowering surface pressures over the continents and enhancing the monsoon precipitation over Venezuela, East Africa and Southern Asia. The land surlitce becomes drier in mid-latitudes and wetter over most of the tropics. This is consistent with estimates of lake levels for the period which are lower than average in rnidlatitudes and above average in the tropics. Although the broad pattern of simulated changes is m agreement with palaeoclimatic data, there are discrepancies, as over West Africa, where the model produces a drier surface at 9 Kbp, whereas the lake level data suggest that it was wetter then. This shortcoming has been the subject of further investigation [44].
9. C O N C L U D I N G REMARKS
General circulation models have been used to investigate the climatic effects of a wide variety of other phenomena including sea surface temperature and sea-ice anomalies [45], changes in land surface characteristics due to desertification or deforestation [46], "'nuclear winter" [47], massive oil fires [48], and waste heat from energy parks. Experiments have also been carried out to determine the influence of topography, land sea contrasts and so forth, on tile general circulation of the atmosphere. Although the use of climate models has become more frequent, each experiment should still be analysed carefully before attempts are made to interpret the results. In doing so, the limitations of the model must be considered and how such limitations will distort the simulated response. One can attempt to do this by isolating the mechanisms producing the changes in climate in the model, and assessing the physical realism of each step. Where there is some uncertainty concerning a parametrization on which the model's response is dependent, the experiment can be repeated using alternative forms of that parametrization to determine whether or not the uncertainties affect the results. One also has to consider whether or not all the physical processes relevant to the experiment have been included in the model. In short, one should always treat results from numerical models with a certain amount of scepticism until they arc supported by a critical assessment of the model used and the simulated response. Acknowh, d#ements --The development, running and assessment of climate models is not a task that can be carried out by an individual. I am indebted to members of the Dynamical Climatology Branch of the Meteorological Oltice (now part
J. F. B. MITCHELL
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of the Hadley Centre) over the last 10 years for their help and support. This is an updated version of an article which appeared in Climate and Global Change (Edited by J. Duplessy, A. Pons and R. Fantechi), Commission of the European Communities (199 I).
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09613 1481/93 $6.00 + . 0 0 Pergamon Press Ltd
SIMULATION OF CLIMATE CHANGE J. F. B. MITCHELL Hadley Centre for Climate Prediction and Research, Meteorological Office, Bracknell RGI2 2SZ, U.K. Abstract The use of climate models to understand and predict climate change is described, using examples fiom numerical studies of the effects of enhanced atmospheric CO,.
I. I N T R O D U C T I O N - - W H Y M O D E L CLIMATE?
2. T H E " G R E E N H O U S E " EFFECT
The increases in atmospheric Greenhouse gases since 1795 have a radiative effect equivalent to a 60% increase in carbon dioxide concentrations, and by early next century, are expected to be equivalent to a doubling of carbon dioxide concentration. Simulations with detailed climate models indicate that this would produce a warming of 2 5 K in global mean surface temperature at equilibrium, with accompanying changes in precipitation, sea level and other parameters. The observed increase of 0.5 K since 1900 is consistent with the lower range of the estimated potential increase, allowing for a possible slowing of the global mean warming due to the ocean's large thermal inertia. Thus, man-made climate change is not just a possibility, it may already be occurring. Consequently, there is an ever pressing need to predict the likely changes in climate due to increases in trace gases in order to guide future energy policies and to minimize the possible climatic impacts. Detailed three-dimensional models of climate are the most promising method of providing the detailed information required for climatic impact assessment. There is also considerable interest as to why the earth's climate has changed in the past. Climate models provide a means of testing theories of climate change. Conversely, periods from which reliable and wide-spread palaeoclimatic data are available may be used as a test of the fidelity of climate models, especially if the factors producing the climatic change arc well known. This paper gives a brief review of work up to the time of the IPCC report (Houghton et al. [1], to which the reader is referred for a more detailed text) and includes references to results obtained since then. Note that examples are taken predominantly from Meteorological Office studies.
The globally averaged radiative heat balance of the earth atmosphere system may be approximated by (S0/4)(1--:0 = r~T~,4
(1)
where So is the solar "constant", 7 is the fraction of solar radiation reflected by the earth and atmosphere, a is Stefan's constant and T,. is the mean or effective radiative temperature of the system. T,. is the radiative equilibrium temperature that the earth's surface would reach if the atmosphere was transparent to longwave (thermal or infrared) radiation. With the current value of ~ (0.3), T,. = 255 K, ( - 18 C) some 33 K below the current observed global mean surface temperature. Now consider a single layer atmosphere, longwave emissivity c and shortwave albedo ~ in radiative equilibrium with the surface (Fig. 1). For convenience, it will be assumed that the atmosphere does not absorb solar radiation. The surface temperature T, is given by T 4 = T~ 4// ( l - e / 2 )
(2)
and the atmospheric temperature T is given by T 4
,]-4 =
}.
(31
Thus, gases which absorb and emit long-wave radiation (greenhouse gases) warm the surface and cool the atmosphere. As an exercise, the reader can show that in a two-level atmosphere in radiative equilibrium, temperature decreases with height. In practice, the troposphere is not generally in radiative equilibrium, but is heated convectively from the surface. The global mean lapse rate, about 6 C/kin, is 433
434
J. F. B. MITCHELL
( T ATMOSPHERE Eo-T4 T. SURFACE Fig. l. In an idealized single layer atmosphere, reflectivity ~, long wave emissivity e and temperature T in radiative equilibrium with the surface at temperature T,.
slightly less than the dry adiabatic lapse rate due to latent heat released in regions of saturated ascent. The radiative equilibrium temperature of - 1 8 " C corresponds to a height of 5.5 km (point a on the solid profile in Fig. 2). An increase in the concentration of greenhouse gases raises the effective emitting level, (point b in Fig. 2) and reduces the effective emitting temperature Tc and outgoing radiance a t e . The system warms until the temperature at the new emitting level rises to the original value T~ (point c). The stratosphere will cool if the concentration of greenhouse gases there is increased. The stratosphere is not convectively coupled to the surface but is in radiative equilibrium; an increase in long wave absorbers will produce enhanced emission to space which at equilibrium is compensated by a fall in emitting temperature. 3. THE PRINCIPAL ABSORBERS, PAST, PRESENT AND FUTURE
The concentration and radiative characteristics of the climatically most important long-wave absorbers
121
E
~
"/~
STRATOSPHERE
'°r/EnhancedC,~ ',,.°~. 8 r-6
Present I \~. -~ !n t. '~.~o¢ 4 Meanradiating ~%.",.-oheights..... ~0~°00 0
I
220
I
2,o
I
26o
TROPOSPHERE
I ~ ~1 SURFACE
28o
300
255 288 Temperature(K) Fig. 2. The effect on vertical temperature profile of increasing atmospheric COz concentrations (schematic). Increasing CO2 raises the emitting level from a to b, and the profile then warms from b to c to restore the effective emitting temperature to its original value.
in the contemporary atmosphere are listed in Table 1, based on Dickinson and Cicerone [2] and Ramanathan et al. [3]. The greenhouse heating is defined as the change in net downward flux at the tropopause due to the presence of each gas. Since increasing the concentration of greenhouse gases produces a slight increase in the downward flux from the stratosphere, the change in net flux at the tropopause rather than at the top of the atmosphere is considered [9]. Note that the troposphere and surface are strongly coupled and hence can be regarded as a single system. Water vapour is by far the most important Greenhouse gas, followed by carbon dioxide. Although the concentrations of chlorofluorocarbons (CFCs) C F C l l and CFC12 are 10 6 that of carbon dioxide, their contribution to radiative heating is only a factor 103 less. These gases have absorption bands which are both very strong and lie in the atmospheric "window" from about 833 cm ~ to 1250 cm ~, where there is little absorption by other gases. Also shown in Table 1 are estimates of the atmospheric lifetimes--note the long lifetimes of CFCs. Estimates of pre-industrial (1795) concentrations of the main trace gases (other than water vapour) are shown in Table 2. The concentrations of carbon dioxide, methane and nitrous oxide are deduced from ice-core sampling. CFCs are produced solely by industrial activity so their pre-industrial concentration is zero. Gases other than CO_, produce over 30% of the radiative perturbation to date, and the total effect already exceeds that due to doubling carbon dioxide concentrations. Estimates of the concentrations of gases in 2025 based on the IPCC "Business-as-usual" scenario are given in Table 2, along with the increase in greenhouse forcing. There is considerable uncertainty in these estimates the first three gases in Table 2 undergo natural cycles which are not completely understood, and for all gases, the industrial contribution is dependent on the world economy and the effectiveness of recent agreements to limit production such as those for CFCs. If the estimates in Table 2 are not greatly in error, the radiative effect of the increases in all gases since the industrial revolution to 2025 will be equivalent to a doubling of CO,. Note the contribution from HCFCs, which have a similar radiative effect to CFCs, but a much shorter lifetime (typically 15 years). The effect of alternative scenarios can be estimated from Table 2 by noting that the radiative effect of carbon dioxide varies approximately logarithmically with concentration [6] and that of methane and nitrous oxide as the square root of their concentration. The effect of C F C I I and CFC12 vary linearly with
Simulation of climate change
435
Table 1. Current concentrations and "greenhouse heating" due to trace gases. The main absorption bands and band strengths (a measure of the probability of a molecule absorbing a photon at the band wavelength) are shown for the less abundant gases and, where appropriate, an estimate of the atmospheric lifetime Principal absorption bands
Gas
Concentration (ppm)
Water vapour Carbon dioxide Methane Nitrous oxide Ozone CFCI I
-3000 353 1.7 0.30 10 100xl0 3 0.22 x 10 3
10 150
0.38xi0 '
13(t
CFCI2
Lifetime (years)
65
c o n c e n t r a t i o n because of their low c o n c e n t r a t i o n s a n d the fact t h a t they a b s o r b at wavelengths where there is little a b s o r p t i o n by other gases.
4. CLIMATE FEEDBACKS IN C A R B O N DIOXIDE EXPERIMENTS
The radiative p e r t u r b a t i o n due to e n h a n c i n g trace gases can (in principle) be calculated to any desired accuracy. D o u b l i n g c a r b o n dioxide a m o u n t s increases the heating o f the t r o p o p a u s e and surface by 4 W m ~ [7] which, assuming the current climate system behaves as a black body at m e a n t e m p e r a t u r e s near 255 K, would produce a w a r m i n g o f 1 . 1 C . However, the a t m o s p h e r i c response to changes in radiative heating is complex involving m a n y processes which are not well understood. These m a y amplify the p e r t u r b a t i o n (positive feedbacks) or d a m p it (negative feedbacks).
Position (cm ~)
Strength cm ~(atmcm) t STP
667 1306 1285 1041 846 1085 915 1095 1152
(many bands) 185 235 376 1965 736 1568 1239 836
Greenhouse heating (W m 2) ~ 100 - 50 1.7 1.3 1.3 0.06 0.12
M o s t equilibrium experiments to determine the climatic effects of increases in trace gases have assumed a d o u b l i n g or q u a d r u p l i n g of c a r b o n dioxide concentrations. The vertical profile of the radiative pert u r b a t i o n due to the o t h e r gases in Table 2 is qualitatively similar to that due to increasing c a r b o n dioxide, (except near the t r o p o p a u s e where the m i n o r gases produce a slight w a r m i n g as opposed to a cooling [3, 8] so experiments with increased c a r b o n dioxide only are p r o b a b l y a d e q u a t e to represent the effect of all the gases, given the m a g n i t u d e of other uncertainties. Here and in the next section, we will consider the equilibrium response to d o u b l i n g c a r b o n dioxide concentrations. First. we consider the main climate feedbacks which have been identified in numerical experiments. A w a r m e r a t m o s p h e r e will hold more water vapour, and hence enhance the radiative p e r t u r b a t i o n due to
Table 2. Past and projected greenhouse gas concentrations and associated changes in "'greenhouse" heating AQ
Gas Carbon dioxide Methane Nitrous oxide CFCI1 CFCI2 Total
Assumed 1860 concentration
AQ 1860 to 1985
Estimated 2035 concentration (ppm)
Estimated AQ 1985 2035 (W m :) range
275 1.1 0.28 0 0
1.3 0.4 0.05 0.06 0.12 1.9
475 2.8 0.38 1.6x10 3 2.8x10 ~
1.8 0.5 0.15 0.35 0.69 3.5
436
J . F . B . MITCHELL
carbon dioxide. Higher temperatures reduce the extent of highly reflective snow and ice, and so increase the absorption of solar radiation. In most simulations with increased carbon dioxide, cloud amount decreases, reducing the amount of insolation reflected back to space, and the mean cloud height increases, further enhancing the greenhouse effect. It is also likely that cloud radiative properties may change. An increase in atmospheric moisture would tend to increase cloud water content and hence the reflectivity of cloud, producing a negative feedback. Thick clouds behave as black bodies at infrared wavelengths, but thin high clouds may have an emissivity considerably less than unity. An increase in cloud water would tend to increase the longwave emissivity of high cloud and enhance the greenhouse effect, adding a further positive feedback. The strength of individual feedbacks simulated in GCM experiments has been quantified using a simple zero-dimensional energy balance model dAT C , dt + ; t A T = AQ
(4)
where AQ is the radiative perturbation, AT is the change in surface temperature, C, is the effective heat capacity of the system, and 2 is defined as the feedback parameter. At equilibrium, AT~q = AQ/2. Thus the smaller 2, the greater AT~q, implying a larger positive feedback. Assuming the feedbacks are linear and independent
)t = ~ 2~; 2~ = AQi/AT,.,~
(5)
where i denotes the individual feedbacks, and AQi is the radiative perturbation due to the process i alone. For example, if i denotes changes in water vapour, then AQi is the radiative perturbation due to the increase in water vapour between the perturbed and control simulations, in the absence of changes in other parameters. Typical values for 2i from GCM experiments arc given in Table 3. The water vapour feedback is easily the strongest, and there is good agreement among different models [97] and with observations [I0]. Lindzen [11] argues that "existing climate models have considerable difficulty predicting upper level water vapour", and that the water vapour feedback could even be negative because of drying due to enhanced subsidence accompanying deeper moist convection, but this argument has been widely refuted [12-14] (see also Nature 347, pages 467 and 491). Drying due to enhanced subsidence is evident in isolated regions of the sub tropics in recent Meteorological Office experiments [15], but the net water feedback
Table 3. Analysis of feedbacks and temperature changes due to doubling CO2, based on typical values from GCM experiments Feedback None Water vapour Ice/snow Cloud amount Cloud radiative properties
Strength Temp.change (W m -2 K ~) (cumulative) +3.7 - 1.4 - 0.3 - 0.9 -0.1 0.5
1.1 1.7 2.1 4.0 2.74.5
is strongly positive due to the dominance of other processes). The ice snow albedo feedback simulated by models is small [16], though it should be noted that the representation of sea-ice in current climate models is simplistic. However, even in the case of snow albedo feedback, there is a large variation between the response in different models [17]. Small changes in the amount and radiative properties of clouds can have a large effect on the net heating of our planet [18]. It has even been suggested that a strong negative feedback due to cirrus clouds limits the maximum tropical sea surface temperature in the present climate [19]. Thus, one might expect changes in cloud amounts and radiative properties to produce strong climate feedbacks. Mitchell et al. [20] found that the simulated equilibrium global mean temperature change on doubling CO2 varied from 5.2-1.9'C depending on the cloud prediction scheme employed in their model. Even with the same cloud prediction scheme, different models produce a wide range of climate sensitivities [9], indicating the importance of other aspects of the hydrological cycle which affect cloud, and hence which must be represented accurately. The represenation of cloud and associated processes is the major source of uncertainty in the simulation of climate change due to increases in greenhouse gases. Other feedbacks have been analysed using onedimensional radiative~convective models [21]. However, the reader is warned that the different modelling groups estimate the feedbacks in their experiments in different ways [16]. The main value of feedback analysis is in identifying the proceses which most affect climate sensitivity, and in helping to identify the reasons for discrepancies between models. 5. MECHANISMS OF CLIMATE CHANGE The previous section considered some of the main processes governing global mean climate. In this
Simulation of climate change section, we consider some of the mechanisms which lead to geographical and seasonal variations of climate change, using simulations of the equilibrium response to doubling atmospheric carbon dioxide concentrations as an example. A fuller account is given in Section 5 of the IPCC report [22]. The increases in carbon dioxide and other trace gases have been occurring on time-scales of decades to centuries. It is generally assumed that one can ignore changes in the continental ice sheets on this time scale, but not changes in the ocean or sea-ice. Coupled ocean-atmosphere models have until recently been prohibitively expensive to run to equilibrium, so over the last decade atmospheric models coupled to a simple oceanic mixed layer of prescribed depth have been used to model the effects of increased CO_~. In order to allow for the advection of heat by the oceans, some models have included a prescribed oceanic heat flux C such that the mixed layer temperature Tis given by dT ph(7~ dt = S + C
(6)
where p, h and Cp are, respectively, the density, depth and specific heat of the well mixed layer and S is the net downward heat flux from the atmosphere. C may
437
be derived by prescribing the sea (surface) temperature, T t¥om climatology in the atmospheric model and integrating through several annual cycles to determine S as a function of time of year and location. Knowing S, h and dT/dt, one can derive C as a function of time and space, and prescribe it in eq. (6) to determine the evolution of T in the coupled atmosphere mixed layer model. Increasing carbon dioxide concentrations leads to a warming of the troposphere and a cooling of the stratosphere (Fig. 3). In the tropics, the tropospheric warming increases with height, since in low latitudes the lapse rate adjusts towards the moist adiabatic which decreases with increasing temperature. The increase in warming with height is more pronounced in models with penetrative convection schemes as opposed to those with moist convective adjustment. Penetrative schemes are more efficient in transporting moisture upwards, and hence in wanning upper levels [23]. In high latitudes in winter, the low-level inversion confines the warming near the surface. The reduction of snow and sea-ice leads to considerable enhancement of the warming in high latitudes in the winter hemisphere. Note that the remowd of sca-ice in sum-
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met leads to increased absorption of solar radiation and storage of heat in the mixed layer, delaying the onset of freezing in autumn and early winter [16, 24]. This leads to a pronounced warming, or more precisely, a reduced cooling relative to the control. In contrast, over sea-ice in summer, temperatures generally rise to the melting point of ice and are maintained there in both the control and anomaly simulation. Even where sea-ice is temporally removed in summer, the thermal inertia of the oceanic mixed layer substantially reduces the magnitude of the warming. The influence of sea-ice is seen more clearly in the geographical distributions of seasonal mean changes in surface temperature (Fig. 4). During December to February the maximum warming occurs in the Arctic, Hudson Bay and near Kamchatka where sea-ice is thinner or removed altogether in the 2 x CO2 simulation, and the minimum occurs over Antarctic sea-ice in the Ross and Weddell Seas. In models in which seaice extents are excessive in the simulation of present day climate, the high latitude warming is exaggerated and the latitude of the maximum warming may be displaced equatorwards. The warming is generally less over the ocean than over land. Over land, evaporation may be limited by the dryness of the surface so that a greater proportion of the increase in radiative heating is used to raise surface temperature as opposed to increasing evaporation. In middle latitudes in winter, removal of snow in the 2 x C O 2 simulation also enhances the surface warming. The warming is a minimum over the tropical oceans. The saturation vapour pressure for water increases exponentially with temperature, so assuming the relative humidity is approximatly constant, potential evaporation also increases non-linearly with temperature. As a result more of the increase in radiative heating of the surface is converted to latent heat and less to raising surface temperatures and sensible heat as one goes from cold to warm regions. Increased evaporative cooling at the surface is linked to increased warming due to latent heat aloft, consistent with the reduction in lapse rate in the tropics noted above. Changes in cloud are qualitively similar from model to model [25]. In general, there is an increase in high cloud and a reduction in upper and middle and tropospheric cloud which is most pronounced in the tropics and mid-latitudes. This is due to an upward shift of the tropopause and the maximum in cloud in the upper troposphere [26, 27]. The changes in low cloud vary considerably from model to model, though increases in low cloud are generally restricted to middle and high latitudes. Thus in low latitudes, where insolation is greatest, there is a reduction in
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planetary albedo (high cloud is generally assigned a low albedo) leading to enhanced absorption of solar radiation, and in the extratropics, there are substantial increases in high cloud tending to reduce longwave cooling to space. On changing from a cloud prediction scheme based on relative humidity to one based on cloud water, Mitchell et al. [20] found large increases in low cloud in the extratropics, due to ice cloud being replaced by water cloud with a longer lifetime. This weakened the solar feedback, and reduced the equilibrium warming from 5.2 to 2.7 K. The warming of the atmosphere is accompanied by an increase in specific humidity (typically 6 % / C warming, which corresponds to relative humidity remaining almost constant) and in evaporation and precipitation (typically about 3 % / C warming). Precipitation does not increase everywhere, and the spatial scale of the change is smaller than for temperature. Whereas there is substantial agreement between the temperature changes simulated by different models, there is little agreement between the regional details of the changes in precipitation, especially in the tropics. All models produce increased precipitation in high latitudes, particularly in winter. The increase in water vapour produces an increase in the transport of moisture into high latitudes, giving enhanced moisture convergence and precipitation. Most models simulate areas of decreased precipitation outside the intertropical convergence zone (ITCZ) and the subtropics,
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Spring and earlier Summer and, in high latitudes, earlier snowmelt and associated runoff. In some models, the soil moisture content may be further diminished due to reductions in cloud giving stronger solar heating at the surface, or to decrease in summer precipitation [29]. Mitchell and Warrilow [30] found that the "summer drying" in the more northerly latitudes could be reversed if simulated snowmelt over frozen ground was lost as runoff, rather than contributing to the local soil moisture content, indicating that the details of the changes are sensitive to the land surface parametrization used.
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J . F . B . MITCHELL
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6. M O D E L L I N G T H E T R A N S I E N T R E S P O N S E TO I N C R E A S E S IN TRACE GASES
Although the concentration of greenhouse gases has and will continue to increase gradually, the temperature response of the atmosphere is likely to be slowed down by the large thermal inertia of the ocean. If the oceans are assumed to have a constant heat capacity C, [eq. (4)], then the evolution of the temperature change AT due to an instantaneous increase in heating AQ at t = 0 is given by AT = A ? (1 - exp ( - At~C,)). z
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The time T taken to reach ( l - l / e ) of the equilibrium response is C,/2. Assuming 2 = 1 W m 2 K - i and that the warming is mixed uniformly through the deep ocean, v is about 500 years. On the other hand, if the warming is confined to the observed seasonal ocean mixed layer which as a depth of order 100 m, then z is of order 10 years. These two estimates are probably upper and lower limits, respectively, and the actual time scale for the oceans depends on the efficiency with which heat is mixed into the deep ocean and so varies between different parts of the ocean. Manabe et al. [31] have compared the equilibrium response to doubling atmospheric CO2 simulated using a mixed layer ocean with the transient response due to a gradual doubling of CO2 over 70 years using the same model, but the deep ocean included. The inertia of the ocean is such that the globally averaged transient warming is about 70% of the equilibrium warming. However, around the southern circumpolar ocean and the northern north Atlantic, the transient response falls below 40% of the equilibrium response. In these regions, the ocean circulation mixes heat absorbed at the surface through the depth of the ocean, slowing up the rate of warming. Qualitatively similar results have been found using other models (at the Max Planck Institute [32] and the Hadley Centre). Manabe et al. [31] note that apart from western Europe and the southern oceans, the patterns of change are similar to that found in their equilibrium experiment, and remain so through the 100 years of the experiment. The rate of warming will depend on the climate sensitivity 2 [see eq. (7)]. This is illustrated by considering the response of a simple climate model to the increases in greenhouse gases prescribed in IPCC Scenario A [l] which gives an effective doubling of CO2 by 2020 and a quadrupling by 2070. For equilibrium sensitive to doubling CO2 of 1.5, 2.5 and 4.5~'C, the projected rates of warming are 0.2, 0.3 and 0 . 5 C per decade, respectively (Fig. 6).
7. U N C E R T A I N T I E S IN THE S I M U L A T I O N A N D DETECTION OF T H E CLIMATIC EFFECT OF INCREASES IN TRACE GASES
(a) There are uncertainties in the pre-industrial concentration of carbon dioxide, and hence in the change in radiative forcing since then. (b) The size of the equilibrium response to a given increase in gases is known only within a factor of 2 or so (Table 3), due mainly to uncertainties in the modelling of cloud and cloud radiative properties. These problems are currently an area of intensive research. The nature of the regional response, particularly in the hydrological cycle, varies from model to model. These discrepancies may be be reduced by using higher horizontal resolution and improved physical parametrizations. (c) There is much to learn concerning the vertical mixing of heat in the oceans and its representation in numerical models. It is not known whether or not one has to resolve oceanic eddies in order to produce a reliable simulation of the changes in oceanic heat transport. Current global ocean GCMs have a horizontal resolution of 300 500 km. These require large horizontal diffusion coefficients maintain numerical stability but also smooth out the more intense ocean currents. (d) The climatic effects of enhanced trace gas concentrations have to be detected against the background of the natural variability of the atmosphere and ocean. The instrumental temperature record exhibits variability on time scales up to several decades. Some indication of the inherent variability of climate on the decadal time scales may be obtained from long (of order 100 years) simulations of coupled ocean atmosphere models (for example, Fig. 7). This natural variability may have enhanced or reduced any warming due to greenhouse gases. (e) There remains the possibility that other factors are masking (or enhancing) the effects of increases in greenhouse gases. There has been much speculation concerning the possibility of changes in the solar "constant". Accurate measurements of the solar constant have been available only for the last decade or so, and these indicate a decrease of less than 0.1% between 1980 and 1986 [33]. (The climatic effect of a 2% increase in solar constant is thought to be approximately equivalent to that due to doubling carbon dioxide concentrations--[34]). This short time variability is associated with the 11 year sunspot cycle, and assuming that the relationship between the measured variations and sunspot number holds for various sunspot cycles, the variations in solar intensity due to this mechanism has always been less than 0.1% on a
Simulation of climate change decadal timescale. There may be variations on a longer time-scale [35, 36] but the evidence is largely speculative and unquantifled. Evaluations of the impact of solar variability on recent climate are given by Shine el al. [5], Hansen and Laicis [34] and Kelly and Wigley [38], who all conclude that the effects are probably small relative to those of increases in trace gases (Fig. 8). Variations in the concentration and composition of stratospheric aerosol resulting from volcanic eruptions have also been cited as a cause of climatic change, but the indices used to categorize volcanic dust do not allow a good quantitative estimate of the associated radiative effects. Estimates of the radiative cooling due to man-made aerosols [37] suggest that their effect is small relative to that of increases in greenhouse gases. Wigley [39] has pursued speculation that increases in sulphate aerosol from fossil fuel emissions would tend to cool climate, both through their direct radiative effect, and through increasing the reflectivity of cloud by acting as cloud condensation nucleii [40]. However, uncertainties in the concentrations of man-made sulphate aerosols and a lack of quantifiable relationship between aerosol concentration and cloud albedo are such that the possibility of significant climatic effects remain speculative. 8. SIMULATION OF PAST CLIMATE In order to try and limit some of the uncertainties discussed in the previous section, attempts have been made to model past climates and compare the simulated changes with the changes from the present deduced fi'om palaeoclimatic data. Models have also been used to help understand past climates [41]. The two periods chosen most frequently are the last glacial maximum (18 Kbp, i.e. 18,000 years before present) and part of the Holocene around 9 Kbp. During the latter period, perihelion almost coincided with the summer as opposed to the winter solstice, enhancing insolation during the northern summer, especially in high northern latitudes. Here, a brief summary of some recent simulations for 9 Kbp [42, 43], will be given. This period is of interest because of the following reasons. (a) The changes in boundary conditions are simple : the changes in orbital parameters are well known, C O , concentrations are believed to have been similar to present, and the ice sheet over North America was relatively small in extent. (b) There is a large amount of palaeoclimatic data available froln that period. In the initial experiment, only the orbital parameters were altered. The enhanced insolation during
443
the boreal summer produces an increase in surface temperature over the northern mid-latitude continents. This enhances the land sea contrast, lowering surface pressures over the continents and enhancing the monsoon precipitation over Venezuela, East Africa and Southern Asia. The land surlitce becomes drier in mid-latitudes and wetter over most of the tropics. This is consistent with estimates of lake levels for the period which are lower than average in rnidlatitudes and above average in the tropics. Although the broad pattern of simulated changes is m agreement with palaeoclimatic data, there are discrepancies, as over West Africa, where the model produces a drier surface at 9 Kbp, whereas the lake level data suggest that it was wetter then. This shortcoming has been the subject of further investigation [44].
9. C O N C L U D I N G REMARKS
General circulation models have been used to investigate the climatic effects of a wide variety of other phenomena including sea surface temperature and sea-ice anomalies [45], changes in land surface characteristics due to desertification or deforestation [46], "'nuclear winter" [47], massive oil fires [48], and waste heat from energy parks. Experiments have also been carried out to determine the influence of topography, land sea contrasts and so forth, on tile general circulation of the atmosphere. Although the use of climate models has become more frequent, each experiment should still be analysed carefully before attempts are made to interpret the results. In doing so, the limitations of the model must be considered and how such limitations will distort the simulated response. One can attempt to do this by isolating the mechanisms producing the changes in climate in the model, and assessing the physical realism of each step. Where there is some uncertainty concerning a parametrization on which the model's response is dependent, the experiment can be repeated using alternative forms of that parametrization to determine whether or not the uncertainties affect the results. One also has to consider whether or not all the physical processes relevant to the experiment have been included in the model. In short, one should always treat results from numerical models with a certain amount of scepticism until they arc supported by a critical assessment of the model used and the simulated response. Acknowh, d#ements --The development, running and assessment of climate models is not a task that can be carried out by an individual. I am indebted to members of the Dynamical Climatology Branch of the Meteorological Oltice (now part
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of the Hadley Centre) over the last 10 years for their help and support. This is an updated version of an article which appeared in Climate and Global Change (Edited by J. Duplessy, A. Pons and R. Fantechi), Commission of the European Communities (199 I).
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43. J. F. B. Mitchell, Greenhouse warming : is the Holocene a good analogue? J. Climate 3, 1177 I t92 11990). 44. F. A. Street-Perrott, J. F. B. Mitchell, D. S. Marchand and J. S. Brunner, Milankovitch and albedo forcing o1" the tropical monsoons. A comparison of geological evidence and numerical simulations for 9000 y BP. rrans R. Soc. Edinburqh Earth Sciences 81,407 427 ([990). 45. C. K. Folland, J. Owen, M. N. Ward and A. Coleman, Prediction of seasonal rainfall in the Sahel region using empirical and dynamical methods. J. Foreca.~tmg 10, 21 56 (1991). 46. J. Lean and D. A. Warrilow, Simulation of the regional impact of Amazonian deforestation. Nature 342, 41 I 413 (1989). 47. R. P. Turco, O. B. Toon, T. P. Ackermam J. B. Pollack and C. Sagan, Climate and smoke: an appraisal of nuclear winter. Science 247, 166 176 (1991/). 48. K. A. Browning, R. J. Allam, S. P. Ballard, R. T. H. Barnes, D. A. Bennetts, R. H. Maryon, P. J. Mason, D. McKenna. J. F. B., Mitchell, C. A. Senior. A. Slingo and F. B. Smith, Environmental effects from burning oil wells in Kuwait. Nature 351,363 367 ( 1991 ). 49. C. A. Wilson and J. F. B. Mitchell, A doubled CO~ climate sensitivity experiment with a G C M including a simple ocean. ,l. Geophys. Res 92. 13315 13343 (1987).