The Earth has been subjected to massive changes since the beginning of its existence. As the planet developed, conditions were altered by both internal and external forces; it is even thought that aerobic bacteria introduced oxygen into the primitive atmosphere (Biello, 2009). Without this bacteria the success of the human race would have been seriously compromised. Earth's atmosphere is constantly interacting with biology, as in this example, but also with its different surfaces of land, sea and ice. These relationships cause feedback loops which may have positive or negative effects on the evolution of climate change. The effects of these feedbacks are slowly being discovered, the results of which may be extrapolated and projected into the future to determine the fate of global climate on a much larger scale. Earth's energy budget plays a key role in climate change feedback mechanisms, namely through the reflectivity of various surface types. This concept will be discussed and applied to various Earth surfaces as well as to atmospheric conditions.
Albedo The sun is the driving force behind all energy on Earth, emitting shortwave radiation from 150 million kilometers away. This incoming solar radiation passes straight through the atmosphere, which absorbs only longwave radiation. The Earth’s surface absorbs insolation and emits longwave radiation in return, and so is able to warm the air above it (see Figure 1). For this reason the amount of insolation the surface absorbs and reflects is critical in determining the Earth’s climate. The ratio of absorption to reflection determines albedo, which is the fraction of incoming solar radiation that is reflected back into space, i.e. not absorbed by the Earth’s surface or atmosphere.
The many different surfaces on Earth all have different albedo values, and even for constant surface types albedo varies with latitude (Henderson-Sellers & Henderson-Sellers, 1975). Earth has an average albedo of 0.3, which indicates that 30% of insolation is reflected back into space before ever being absorbed. Albedo can be quickly and qualitatively evaluated by a visual assessment light- and darkness of a surface; the dark pine needles of evergreen forests may absorb as much as 85% of incident solar radiation (Fu et al, 2008), while new snow reflects almost as much (Arctic Coastal Ice Processes, 2006). Albedo varies broadly across biomes (see Figure 2), but also varies with age, thickness, opacity and surficial debris cover in glacial and sea ice (Curry et al, 1995). The feedback relationship between climate and albedo comes from the ability of the surface to affect atmospheric temperatures. Effects may be seen on a regional scale, but may also contribute to global climate change if albedo shifts occur on a broad scale. Arctic sea ice is a fine example of this; it covers a large area, has little debris cover and, characteristically, has a very influential and high albedo, usually over 0.5 (Arctic Coastal Ice Processes, 2006). As the Arctic ice caps fluctuate seasonally every year, so does solar heat flux at the poles. Less areal ice cover causes less reflection and more absorption, and inherently higher temperatures. This is to be expected on an annual time scale, however long-term trends may have a significant effect on global climate change. For example, if sea ice cover increases annually for 10 years, increasing amounts of insolation will be reflected back into space, causing a decadal decrease in temperatures in the polar region. Sea ice specifically causes a positive feedback; it is self-perpetuating. As ice reflects increasing amounts of insolation back into space, Earth's temperatures continue to decrease. Colder temperatures sustain ice growth, which expands the region of high albedo and promotes cooling on an even larger scale. While it may seem that this would perpetuate Earth into a state of complete ice cover, which some scientists believe has happened in the past (MacDonald, 2010), there are many other factors which help the planet to retaliate.
Vegetation While the reflectivity of ice has a significant contributions on climatic conditions, surfaces with low albedos also affect climate. Vegetation, like ice, exhibits a positive feedback relationship between albedo and climate change but has converse effects. The lower albedos of plants cause them to absorb more insolation and increase the temperature of the surrounding air. It has been suggested that this feedback may account for 10-20% of monthly temperature fluctuations in densely vegetated areas (Liu et al, 2006). Even small changes such as the emergence of leaves in the spring can decrease albedo and cause increased absorption of insolation and raise temperatures (Liu et al, 2006), as in Figure 4.
Albedo values in plants vary widely, ranging from 0.05 in coniferous forests to .25 in grasslands (Budikova et al, 2011), and therefore changes in the type of vegetation in a particular region may in turn cause changes in climate. Variances in vegetation types may occur on natural timelines, but may also be influenced by outside factors such as human intervention. Deforestation, agriculture cultivation, and urban expansion are all means by which humans change the biological characteristics of a region.
Hoffman & Jackson (2000) highlighted atmospheric changes caused by the transition of African savanna into grassland. They found that as civilization expands and trees are harvested or destroyed, the savanna begins to take on grassland characteristics. Grasslands have lower albedo values than savanna and therefore reflect more sunlight. Grasses also have a different biological make-up and survival techniques than trees that are found in the savanna. Decreasing woody plant cover not only affects the albedo of the region, but also may cause a decrease in precipitation over time (Hoffman & Jackson, 2000). Changes in rainfall affect soil moisture content, runoff, evapotranspiration and water vapor exchange with the atmosphere. Energy exchange on land depends on each of these factors (Foley et al, 1998), and each one may influence climate via a feedback cycle that is either positive or negative. Deforestation, for example, leads to decreased precipitation amounts and makes it harder for woody vegetation to survive in the region; this further decreases the amount of trees in the area. Grasses can survive more successfully in drier conditions, so the transformation of the region into grasslands will be supported by the drier atmosphere. Lower moisture flux into an area signifies less cloud cover, perpetuating the decreasing frequency of precipitation and allowing more insolation to pass through the atmosphere to be absorbed by the surface.
Vegetation affects climate in ways other than albedo; plants exchange gases and moisture with the environment. Carbon dioxide that resides in soil is one of the largest sources of the gas from any terrestrial ecosystem (Metcalf et al, 2011), and plants continually take up and store CO2 from the atmosphere. When plants are destroyed, i.e. during deforestation, the gas is released again. Feedback cycles can be recognized with respect gas exchange as well. A simple example assumes that vegetation is the only factor in influencing climate. Vegetation generally thrives in moisture-rich areas, and in a warm and wet environment plants grow quickly and easily. However, as the plant community grows and expands it takes up more and more insulating CO2 from the atmosphere, which causes cooling effects. As temperatures cool, the colder air loses capacity to hold moisture and the climate becomes continually cooler and drier. In this new environment, the plant community will suffer because climatic conditions are not keen to their survival. As vegetation struggles and the community wanes, there are fewer organisms to take in CO2. With time CO2 concentrations in the atmosphere will rise, promoting once again a warmer environment. In actuality, vegetation is not the only factor that influences climate, so this example is unrealistic. Nonetheless, this feedback does play its part in global climate change.
Clouds The significance of the relationship between clouds and climate change is debatable; some believe that it is not a strong feedback mechanism at all (Schneider, 1972; Cess, 1976). Cloud coverage affects climate in two, seemingly contradictive ways. Clouds have a relatively high albedo averaged around 0.5 (Cess, 1976), which suggests areas that are cloudy for long periods of time will be subject to lower amounts of insolation. While clouds reflect incoming radiation, they also block outgoing radiation that is coming from the Earth’s surface (see Figure 1). This creates a blanket effect over the given area, keeping the surface at a relatively constant temperature until the clouds dissipate and normal heat flux is restored. For this reason, initial conditions are very important when assessing the effects cloud coverage has on climate change.
Whether cloudiness has a positive or negative feedback with climate is dependent on many things. Generally, cloud cover decreases surface temperatures by reflecting insolation back into space before it ever reaches the ground. This assumes that the surface over which the clouds lie has an albedo less than that of the clouds themselves. In polar regions where environments experience significant snow and/or ice cover, the albedo of clouds may be greater than that of the surface. In this situation enhanced cloud cover may cause an increase in temperatures rather than a decrease (Schneider, 1972). The same effect may be caused by seasonal variations in surface albedo as well, whether it be snow cover, leaf fall, annual melting or flooding of a region, etc.
In most cases the albedo of clouds is less than that of the surface, but within the realm of cloud types albedos vary. Higher clouds typically hold higher albedo values. They are colder, brighter, and reflect more insolation (Figure 3). Lower clouds are warmer and emit more blackbody radiation than their higher companions, therefore having a smaller reflectivity and lower albedo (Schneider, 1972). To add to this, low clouds are usually thicker, and their position close to the surface allows them to trap outgoing longwave radiation emitted from the Earth. In this case cloud cover does not have a cooling effect, it instead insulates the surface. Due to their position, high clouds do not have insulating effects, nor do they have depth substantial enough to trap outgoing radiation. The nature of cloud cover over a given region will affect the amount of insolation received and emitted from the surface, and its effects on climate change will depend on these factors.
Variations in cloudiness and cloud type cause several contradicting effects on climate conditions. Therefore, fluctuations in such are not reliable means of forecasting climate change on a global scale. Scientists recognize that temperature changes caused by effects on radiative flux due to cloudiness are minimal, and any changes in temperatures seen in long-term observations and modeling experiments may likely be from other sources (Schneider, 1972; Henderson-Sellers & Henderson-Sellers, 1975; Cess, 1976).
Earth’s atmospheric and environmental conditions are constantly changing and interacting. These conditions cause daily local variations of weather, such as cloudiness and rainfall, which may vary on a wide range of time and areal scales. One feedback mechanism alone cannot cause significant climate change on a global scale (Liu et al, 2006; Schneider, 1972; Henderson-Sellers & Henderson-Sellers, 1975; Cess, 1976). Seasonal variations may cause a feedback to be positive in spring and negative in fall, or one mechanism may exhibit positive feedback if another is not present, but negative if another is. For example, in spring the albedo of forested areas decreases as leaves reappear, which serves as a warming mechanism; however in the late summer evapotranspiration cooling effects trump albedo and temperatures begin to drop (Liu et al, 2006). Interaction between feedback mechanisms is just as important, if not more, as the existence of the feedback itself. One effect the existence of individual mechanisms may have on climate change is the rate at which it happens. Foley, et al (1998) believe the addition of one factor to a set of preexisting conditions that are favorable for climate change may act as a tipping point, and a possible cause for sudden shifts in the global environment.
Many feedback relationships have shown to be counterintuitive or to go against the general consensus. The Hoffman & Jackson (2000) example on African savanna and grassland met one major shortfall in its findings. The albedo of grasslands, as previously mentioned, has a higher value than that of wooded areas. In theory, grassland reflects more sunlight back into the atmosphere and decreases surface temperatures. To explain this anomaly the initial conditions of the savanna need to be evaluated, specifically the fact that the savanna experienced regular rainfall and cloud cover prior to the transition into grassland. Cloud cover associated with the precipitation would have reflected sunlight back into space before it ever got a chance to be absorbed or reflected by the surface. The reflectivity of clouds over the savanna was enough to locally overwhelm the effects of the imposing grasslands, which brough a higher surface albedo to the region. This caused the area to experience an increase of temperature of about 1°C instead of the expected decrease (Hoffman & Jackson, 2000).
Computer models are used to produce a first guess at long-term effects feedback mechanisms have on climate change, Rarely, if ever, are these models able to take into account all possible mechanisms (Curry et al, 1995). Even if a model could predict the areal coverage of sea ice, it may not be able to take into account its thickness. Albedo in sea ice can vary significantly with thickness, and ice less than 2 m in depth can cause temperature increases of more than twice that of only slightly thicker ice (Curry et al, 1995). Sea ice and albedo exhibit a positive feedback and promote ice expansion, but its demise could be met by warming seas, increasing greenhouse gases or other factors unrelated to albedo. Negative feedback relationships could cause frequent or sudden fluctuations in Earth’s conditions, while external influences such as sunspots and Milankovich cycles could interrupt the direction of Earth’s climate change at a given point in time. These outlying factors would also need to be included in numerical prediction to produce a realistic forecast.
Predicting the weather a week from now is difficult, even with high resolution models and an extensive grid of observations around the globe; predicting the climate in one hundred or even one thousand years gets increasingly complicated. As we enter an era where causes of climate change are better understood, we also understand its complexity. Extrapolating the state of deciduous forest cover thousands of years from now is challenging enough, let alone finding the same fate of all other biome environments, ice cover and cloudiness. Only when these feedback mechanisms become better understood, and technology advances to the point where more factors may be considered in numerical prediction, will there be a more definitive grasp on long-term effects of internal planetary interactions.