Climate Models, Climate Change and Feedback Processes
First let’s take a quick look at reliability of the models used to make projections of future climate change:
Global mean near-surface temperatures over the 20th century from observations (black) and as obtained from 58 simulations produced by 14 different climate models driven by both natural and human-caused factors that influence climate (yellow). The mean of all these runs is also shown (thick red line). Temperature anomalies are shown relative to the 1901 to 1950 mean. Vertical grey lines indicate the timing of major volcanic eruptions.
Next let’s take a quick look at the projections of future climate change that these models make (IPCC, 2007):
The figure below show the multi-model averages and assessed ranges for surface warming and the table summarizes the projected global average surface warming and sea level rise at the end of the 21st century. In the figure, solid lines are multi-model global averages of surface warming (relative to 1980–1999) for the scenarios A2, A1B and B1, shown as continuations of the 20th century simulations. Shading denotes the ±1 standard deviation range of individual model annual averages. The orange line is for the experiment where concentrations were held constant at year 2000 values. The grey bars at right indicate the best estimate (solid line within each bar) and the likely range assessed for the six SRES marker scenarios. The assessment of the best estimate and likely ranges in the grey bars includes the AOGCMs in the left part of the figure, as well as results from a hierarchy of independent models and observational constraints.
The text box below lists the scenarios that are in current use.
How well do we Understand Climate Feedback Processes?
A Review Article by: Sandrine Bony, Robert Colman, Vladimir M. Kattsov, Richard P. Allan, Christopher S. Bretherton, Jean-Louis Dufresne, Alex Hall, Stephane Hallegatte, Marika M. Holland, William Ingram, David A. Randall, Brian J. Soden, George Tselioudis, and Mark J. Webb. Journal of Climate, Vol. 19, 3445-3482, August 2006.
1. Abstract/Introduction
This review addresses the physical mechanisms involved in climate feedbacks. Climate feedbacks are processes (internal to the climate system) that either amplify or damp the climate response to an external perturbation. The focus of the review is on the feedbacks associated with climate variables (i) that directly affect the top-of-the-atmosphere (TOA) radiation budget, and (ii) that respond to surface temperature mostly through physical (rather than chemical or biochemical – this excludes feedbacks that might be associated with the carbon cycle or with aerosols, for example, and with soil moisture and ocean processes) processes.
Review of Climate Feedbacks
Climate sensitivity estimates depend strongly on radiative feedbacks associated with the interaction of the earth’s radiation budget with water vapor, clouds, temperature lapse rate, and surface albedo in snow and sea ice regions – all feedbacks have a well-established role in General Circulation Models (GCMs) and their estimates of climate sensitivity.
· Water vapor and temperature – positive feedback
· Snow and sea ice and temperature – positive feedback
· lapse-rate and temperature – negative (positive) radiative feedback if a warming is larger (smaller) in the upper troposphere than at low levels, compared to a uniform temperature change
v the stronger the decrease of temperature with height, the larger the greenhouse effect – discuss
· cloud feedbacks – can be positive or negative, uncertain for the most part
Compare quantitative estimates of climate feedbacks – Figure 1:
· water vapor is the strongest feedback (magnitude)
· cloud feedbacks next to WV in strength, followed by surface albedo and lapse rate
· inter-model mean spread is substantial in all cases
· range in strength of response is large for WV and cloud feedbacks
· spread of combined WV and lapse rate feedbacks is ~ ½ of individual feedbacks (anti-correlated)
Summary: cloud feedbacks are very important and are responsible for a large part of the uncertainties associated in climate sensitivity estimates.
It is important to look at the physical mechanisms behind the global estimates of climate feedbacks because that would help us (i) to understand the reasons why climate feedbacks differ or not among models, (ii) to assess the reliability of the feedbacks produced by the different models, and (iii) to guide the development of strategies of model–data comparison relevant for observationally constraining some components of the global feedbacks.
2. Clouds feedbacks
So, where are the clouds?
Fig. 2 illustrates that the atmospheric dynamics (this is: the large-scale organization of the atmosphere) is a strong function of latitude. In the Tropics, large-scale overturning circulations prevail. These are associated with narrow cloudy convective regions and widespread regions of sinking motion in the midtroposphere (generally associated with a free troposphere void of clouds and a cloud-free or cloudy planetary boundary layer). In the extratropics (midlatitudes and such), the atmosphere is organized in large-scale baroclinic disturbances.
FIG. 2. Composite of instantaneous infrared imagery from geostationary satellites (at 1200 UTC 29 Mar 2004) showing the contrast between the large-scale organization of the atmosphere and of the cloudiness in the Tropics and in the extratropics. [From SATMOS (©METEO-FRANCE and Japan Meteorological Agency).
The Tropics:
FIG. 3. Two conceptual representations of the relationship between cloudiness and large-scale atmospheric circulation in the Tropics: (a) structure of the tropical atmosphere, showing the various regimes, approximately as a function of SST (decreasing from left to right) or mean large-scale vertical velocity in the midtroposphere (from mean ascending motions on the left to large-scale sinking motions on the right). [From Emanuel (1994).] (b) Two-box model of the Tropics used by Larson et al. (1999). The warm pool has high convective clouds and the cold pool has boundary layer clouds. Air is rising in the warm pool and sinking across the inversion in the cold pool.
v compare above with mantle convection – here intense and narrow regions of “upwelling” (convective, tall, towering clouds) and broad regions of “downwellings”. Both systems heated from below, mantle has internal heating source also.
A continuous look at the same conceptual model is summarized in the figure below. To study vertical motion in the atmosphere one can use the vertical velocity (defined as in a Cartesian coordinate system, whereis the vertical coordinate) or omega ≡ ω, which is the pressure change (here one uses pressure surfaces instead of height surfaces) following the motion of a parcel, defined as. It can be shown (see the classical textbook by Holton: “An Introduction to Dynamic Meteorology”) that to a very good approximation (namely, for most practical purposes) there is a simple and direct equivalency between and:, where ρ is the density andis gravity. Pressure can be measured in pounds/in2 = psi, Pascals, Pa (Newton/m2) or bars (and millibars = mbar). Common in meteorology is the hPa (hecto Pascal) which is equivalent to mbar. Basically, the 500 mbar is the 500 hPa surface.
Here the large-scale vertical velocity ω is used as a proxy for the large scale vertical motions in the atmosphere and to look at the Hadley-Walker circulation in the tropics, assigning statistical weight to the different circulation regimes (ascending versus descending motions and their associated atmospheric vertical structure).
FIG. 4. (a) PDF Pω of the 500-hPa monthly mean large-scale vertical velocity ω500 in the Tropics (30°S–30°N) derived from ERA-40 meteorological reanalyses, and composite of the monthly mean (b) GPCP precipitation and (c) ERBE-derived longwave and shortwave (multiplied by -1) cloud radiative forcing in different circulation regimes defined from ERA-40 ω500 over 1985–89. Vertical bars show the seasonal standard deviation within each regime. [After Bony et al. (2004).]
Considering dynamical regimes defined from ω allows us to classify the tropical regions according to their convective activity, and to segregate in particular regimes of deep convection from regimes of shallow convection. ‘Convection’ is used to describe thermally driven turbulent mixing in the atmosphere. ‘Deep convection’ refers to convection where vertical motion takes parcels from the lower atmosphere to above 500 hPa and it requires low level convergence/upper level divergence, upper level relative humidity in excess of 70%, unstable layer and a triggering mechanism. ‘Shallow convection’ refers to convection where vertical lifting is capped at about 500 hPa, it requires basically the same ingredients as deep convection except that all have to take place in the lower atmosphere and it is then not necessary to have upper level divergence but a mid level cap (a local inversion, for example).
In general terms we might consider the panels as corresponding to the western and eastern parts of the ocean basin, to the left of 0 and to the right of 0, respectively. Panels (b) and (c) are the precipitation and clouds fields (from observations) composited with the regimes determined from the ω fields. The blue arrows in the figure indicate the extreme regimes (tails of the PDF): small weight for areas of strong ascending and areas of the strongest descending motions. This basically says that although there is intense large-scale ascending and sinking motions in the atmosphere, the areas over which that happens are small and so their importance to the general circulation (hence to climate) may not be that important. It is the impact of the largest areas, over which motions may not be so intense, that matters. Panels (b) and (c) must be looked at in conjunction with (a). Panel (c) is the CRF (Cloud Radiative Forcing) in the short wave and long wave parts of the spectrum. The CRF is a very useful quantity (and hence the importance of these composited diagrams) because it integrates all possible effects of clouds: low, high, thick, thin, etc., and hence it tells us about the impact of clouds on climate (not just a sense of amount of clouds, for example). For example, looking at panel (c) we can see that there are areas with a very high value of CRF (both in the SW and LW, the left side of the panel) but when we look at the corresponding values of Pω we see that the values of CRF happen over small areas of the tropics. The same can be said for the other tail-end of the CRF composite with Pω. What the Pω curve is also showing is a maximum occurring over areas of slow descending motion, generally over the eastern part of the ocean basin, (recall the Walker circulation pattern over the Pacific basin). There we also see that the values of CRF are not so big but these areas are very important climatologically. In sum: these studies have been able to show that the most vigorous, convectively speaking, regions may not be the most important climatologically in terms of climate change.
The Extra-tropics:
At midlatitudes, the atmosphere is mostly organized in synoptic weather systems. An idealized baroclinic disturbance is represented in Fig. 5a, (included below) showing the warm and cold fronts outward from the low-level pressure center of the disturbance, together with the occurrence of sinking motion behind the cold front and rising motion ahead of the warm front. The different parts of the system are associated with specific cloud types, ranging from thin low-level cumulus clouds behind the cold front, thin upper-level clouds ahead of the warm front, and thick precipitating clouds over the fronts (Fig. 5b). For good discussion of extratropical weather systems (and much more!), see the book by Wallace and Hobbs (1977).
· Barotropic Atmosphere – one in which the density depends only on the pressure, so that isobaric surfaces are also surfaces of constant density.
· Baroclinic Atmosphere – an atmosphere in which the density depends on both the temperature and the pressure. In a baroclinic atmosphere the geostrophic wind generally has vertical shear and this shear is related to horizontal temperature gradients.
FIG. 5. (top) Schematic of a mature extratropical cyclone represented in the horizontal plane. Shaded areas are regions of precipitation. [From Cotton (1990).] (bottom) Schematic vertical cross section through an extratropical cyclone along the dashed line reported in the top showing typical cloud types and precipitation. [From Cotton (1990), after Houze and Hobbs (1982).]
Notice the transition in the cloud types as you pass through the warm front, cirrus and cirrostratus (green house effect dominates) to alto-stratus and nimbostratus (sheet like, thick cloud base) overall producing a warming effect. On the backside of the low pressure system you have a cold front where the cloud types generally consist of cumulous and cumulonimbus. Once the high pressure settles in cumulus clouds dominate bright high albedo, overall cooling effect.
Given the strong connection between the large-scale atmospheric circulation and the distribution of water vapor and clouds, understanding cloud (and water vapor) feedbacks under climate change requires the examination of at least two main issues: 1) how might the large-scale circulation change under global warming and how might that affect the global mean radiation budget (even without any specific change in the atmospheric properties under given dynamic conditions), and 2) how might the global climate warming affect the water vapor and cloud distributions under specified dynamic conditions.
Understanding of cloud feedback processes:
The Tropics and the extratropics are associated with a large spectrum of cloud types, ranging from low-level boundary layer clouds to deep convective clouds and anvils. Because of their different top altitudes and optical properties, the different cloud types affect the earth’s radiation budget in various ways. Therefore, understanding cloud radiative feedbacks requires an understanding of how a change in climate may affect the distribution of the different cloud types and their radiative properties, and an estimate of the impact of such changes on the earth’s radiation budget.
The main point here is that because the occurrence of the cloud types is controlled by (1) the large-scale atmospheric circulation and by (2) other factors such as surface boundary conditions, boundary layer stratification and wind shear, making the background relationship between cloud properties and large-scale circulation more explicit, it becomes easier to isolate other influences such as the impact of a change in surface temperature or in the thermodynamic structure of the troposphere. The analysis of cloud response (namely, cloud changes) to a climate change can be then explained by the response due to (1) changes in the large-scale flow, and (2) and on the by other factors, such as an intrinsic dependence of cloud properties on temperature. In the Tropics, the dynamics are known to control to a large extent changes in cloudiness and cloud radiative forcing at the regional scale. At the Tropics-wide scale, a change in circulation may change the tropically averaged cloud radiative forcing and radiation budget (even in the absence of any change in cloud properties, namely even in the absence of changes in the thermodynamics) if circulation changes are associated with a global strengthening or a weakening of the Hadley–Walker circulation.