158 Climate management The State University of New York Col- lege of Environmental Science and For- estry (SUNY-ESF) biomass research farm in Tully, New York (Lawrence P. Abraham- son, DOE/NREL) as syngas. Pyrolysis—heating biomass in the absence of oxygen—pro- duces liquid pyrolysis oil. Both syngas and pyrolysis oil can be used as fuels that are cleaner and more ecient than solid biomass. Both can also be converted into other usable fuels and chemicals. As research and discoveries continue and cleaner, more ecient energy sources are discovered and implemented, society advances closer to curbing global warming and its resultant harm to the environment. 159 T he Earth’s climate system is too complex for the human brain to grasp. ere are so many interrelated forces constantly being inu- enced by outside factors and constantly shiing, trying to nd some balance of equilibrium. It is simply not possible to write down a list of equations describing how the climate system works and reacts. e Earth’s climate is not a straightforward process that gets from point A to point B every day in exactly the same way, at the same time, or in the same place. e only consistency about climate is that it is not consis- tent, and that is because there are so many variables involved and the patterns of possible interactions are enormous. One of the key challenges climatologists face today with global warming is that it is important to be able to predict with some sense of condence how the Earth’s climate will change from region to region as temperatures rise so that policy makers can make appropriate deci- sions. Because of the inherent complexity and uncertainty, in order for 8 Climate Modeling 160 Climate management climatologists to be able to do this they need to rely on climate mod- els. Climate models are systems of dierential equations derived from the basic laws of physics, uid motion, and chemistry formulated to be solved on supercomputers. is chapter discusses climate modeling—how it began, its funda- mentals, and the challenges that both climatologists and computer pro- grammers face today in its development. It also explores some of the diverse uses of climate models and how they are helping increase the scientic and public knowledge about global warming. The modeLing ChaLLenge—a brieF hisTory Climatology is a branch of physics, and physics makes use of two very powerful tools: experiments and mathematics. Weather and climate are so complex that without computers it would be impossible to math- ematically quantify the climate system. erefore, up until the com- puter age, there was no way to explain why and how climate behaved as it did. Once the technology developed, it was possible to build and assess quantitative climate models, because climate is based on physical principles. e rst objective of a climate model is to explain—however basi- cally—the world’s climates. Early on, the simplest and most widely accepted model of climate change was self-regulation, which means that changes are only temporary deviations from a natural equilibrium. Beginning in the 1950s, an American team began to model the atmo- sphere as an array of thousands of numbers. To answer the question about carbon, some primitive models were constructed representing the total carbon contained in an ocean layer, in the air, and in vegeta- tion, with elementary equations for the uxes of carbon between the reservoirs. Regardless of the carbon dioxide (CO 2 ) budget, scientists expected that natural feedbacks would operate and automatically read- just the system, restoring the equilibrium. Climatologists also recog- nized the need for more sophisticated models. ey wanted to be able to explain triggers that caused past events, such as ice ages, plate tecton- ics, and changes in the ocean currents. In the 1960s, computer modelers made encouraging progress by being able to make fairly accurate short-range predictions of regional 161 Climate Modeling weather. Modeling long-term climate change for the entire planet, how- ever, was restricted because of insucient computer power, ignorance of key processes such as cloud formation, inability to calculate the crucial ocean circulation, and insucient data on the world’s actual climate. In the 1980s, models had improved enough that Syukuro Manabe, a senior meteorologist at Tokyo University, was able to use them to dis- cover that the Earth’s atmospheric temperature should rise a few degrees if the CO 2 level in the atmosphere doubled. rough the use of models, by the late 1990s, most experts acknowledged global warming and its eects. One area that scientists were interested in being able to model was that of climate surprises—rapid climate changes. One of the most well-known models was an energy budget model developed by William Sellers of the University of Arizona in 1969. He computed possible variations from the average state of the atmosphere separately for each latitude zone. Sellers was able to reproduce the pres- ent climate and was able to document that it showed extreme sensitivity to small changes. He determined that if incoming energy from the Sun decreased by 2 percent (whether due to solar variation or increased dust in the atmosphere), it could trigger another ice age. Based on his results, Sellers suggested that “man’s increasing industrial activities may even- tually lead to a global climate much warmer than today.” Because an entire climate cannot be brought inside a laboratory, the only way to carry on an “experiment” of the entire system is to build a model of the entire system—a proxy. e most unpredictable part of the climate system—and as a result, one of the hardest to model—is the amount of radiation emitted by the Sun and the Earth. At any given time, water is present in water vapor, the oceans, and locked away in ice. e form and position the water takes change constantly in response to its interaction between solar and thermal radiation. Clouds (especially low-lying thick clouds) reect huge amounts of sunlight back into space and keep it from overheating the Earth. High-altitude wispy clouds and water vapor absorb greater amounts of outgoing thermal (heat) radia- tion, which is generated o the Earth’s surface aer it gets warmed by the Sun. In addition to greenhouse gases, clouds and water vapor contribute to keep the Earth’s average temperature comfortably livable year round. 162 Climate management Atmospheric water has a tremendous eect on the Earth’s climate. For years, researchers have been trying to understand all of the complex interactions: specically, how clouds and water vapor will act if global warming escalates and the atmosphere gets hotter. Scientists at the National Aeronautics and Space Administration (NASA) have currently developed several computer models to simulate the interactions between clouds and radiation. e area they are focus- ing most on is the Tropics because that region gets the most sunlight. Results so far have been mixed: Some say in the future low-lying thick clouds will increase, making global warming worse; others say when the Earth’s surface heats up, cirrus clouds will dissipate and allow more thermal energy to escape to outer space. e reason this is so dicult to model consistently is because clouds are constantly shiing, separating, growing, and shrinking. In addition, the only way to study them is through remote sensing (satellite imag- ery), which is still fairly new technology—satellites and image-process- ing soware have only been around about 25 years. Today, some of the “simple” models that can be run on desktop computers are comparable to what was once considered state of the art for even the most advanced computers in the 1960s. As a comparison, the computers used by NASA during the Apollo missions occupied an entire room. Today, those same programs can be run on a desktop computer. Computer models of the coupled atmosphere-land surface- ocean-sea ice system are essential scientic tools for understanding and predicting natural and human-caused changes in the Earth’s climate. FundamenTaLs oF CLimaTe modeLing One of the key reasons climate is such a challenge to model is because it is a large-scale phenomena produced by complicated interactions between many small-scale physical systems. According to Gavin A. Schmidt at NASA’s Goddard Institute for Space Studies (GISS), “Climate projections made with sophisticated computer codes have informed the world’s policy makers about the potential dangers of anthropogenic interference with Earth’s climate system. e task climate modelers have set for themselves is to take their knowledge of the local interactions of air masses, water, energy, and momentum, and from that knowl- edge explain the climate system’s large-scale features, variability, and 163 Climate Modeling The evolution of climate models beginning in the mid-1970s and extending into the near future response to external pressures, or ‘forcings.’ at is a formidable task, and though far from complete, the results so far have been surprisingly successful. us, climatologists have some condence that theirs isn’t a foolhardy endeavor.” It was not until the 1960s that electronic computers were able to meet the extensive numerical demands of even a simple weather sys- tem, such as low pressure and storm front. Since that time, more com- ponents have been added to climate models, making them more robust and complex, such as information characterizing land, oceans, sea ice, atmospheric aerosols, atmospheric chemistry, and the carbon cycle. 164 Climate management Models today are able to answer a wide range of questions, many geared specically toward the eects of global warming. The Physics of Modeling e physics involved in climate models can be divided into three catego- ries: fundamental principles (momentum, properties of mass, conserva- tion of energy); physics theory and approximation (transfer of radiation through the atmosphere, equations of uid motion); and empirically known physics (formulas for known relationships, such as evaporation being a function of wind speed and humidity). Each model has its own unique details and will require several expert judgment calls. e most unique characteristic of climate models is that they have emergent qualities. In other words, when combining several interactions within the model, or parameters, the results of the interaction can produce an emergent quality unique to that system that was not previously obvious when looking at each system component by itself. For instance, there is no mathematical formula that describes the Earth’s equatorial intertropical convergence zone (ITCZ) of tropical rainfall, which occurs through the interaction of two separate phenom- ena (the seasonal solar radiation cycle and the properties of convection). As more components are added to a model, it becomes more complex and can have more possible outcomes. Simplifying the Climate System All models must simplify complex climate systems. One critical aspect of climate models is the detail in which they can reconstruct the part of the world they are trying to portray. is level of detail is called spa- tial resolution. If a climate model has a spatial resolution of 155 miles (250 km), then there are data points draped around the globe like a net with an x/y/z coordinate set spaced on a grid at an interval of 155 miles (250 km). e z-coordinate—representing the vertical height—can vary, however. e resolution of a typical ocean model, for example, is 78–155 miles (125–250 km) in the horizontal (x/y) and 656–1,312 feet (200–400 m) in the vertical (z). Equations are generally solved every simulated “half hour” of a model run. Some of the smaller scale, local- ized processes such as ocean convection or cloud formation have to be 165 Climate Modeling generalized in a process called parametrization; otherwise it would be too demanding on the computer system. ere are three major types of processes that need to be dealt with when constructing a climate model: radiative, dynamic, and sur- face processes. Radiative processes deal with the transfer of radiation through the climate system, such as absorption and reection of sun- light. In other words, where the sunlight travels once it is in the system. Dynamic processes deal with both the horizontal and vertical transfer of energy. is can include processes such as convection (the transfer of heat by vertical movements in the atmosphere, inuenced by den- sity dierences caused by heating from below); diusion (the spreading outward of energy throughout a system); and advection (the horizontal transport of energy through the atmosphere). Surface processes are those processes that involve the interface between the land, ocean, and ice: the eects of albedo (how reective a surface is); emissivity (the ability of a surface to emit radiant energy); and surface-atmosphere energy exchanges. e simplest models have a “zero order” spatial dimension. e cli- mate system is dened by a single global average. Models get more com- plex as they increase in dimensional complexity, from one-dimensional (1-D), to two-dimensional (2-D), to three-dimensional (3-D) models. e complexity of the models is also controlled by changing the spatial resolution. In a 1-D model the number of latitude bands can be limited; in a 2-D model the number of grid points can be limited by spacing the points farther apart in a coarser grid. How long the model is run and the time intervals it is run on also aect the length and volume of the calculations involved. Modeling the Climate Response e purpose of a model is to identify the likely response of the climate system to a change in any of the parameters and processes, which con- trol the state of the system. For example, if CO 2 is added into a simula- tion, the goal of the model is to see how the climate system will respond to it as the climate system tries to nd an equilibrium. Or perhaps a model can focus on glacier melt and the results of ocean circulation as a result of the addition of freshwater and its eect on the climate. 166 CLIMATE MANAGEMENT A climate model is comprised of a set of x/y/z points placed around the globe at specifi ed intervals in a netlike structure, called its resolu- tion. A small grid with lots of points close together has a high resolu- tion and is more detailed; a large grid with points spread farther apart has a low resolution and less detail. In the model, each point x/y/z intersection has a value associated with it—one value for each variable represented in the model. In this example, each grid point would have a distinct value for solar radiation, terrestrial radiation, heat, water, advection, atmosphere, and so on. xvi+264_GW-ClimManage.indd 166 3/12/10 1:08:54 PM 167 Climate Modeling Sometimes, complete processes can be omitted from a model if their contribution is negligible to the timescale being looked at. For instance, if a model is looking at a span of time that lasts only a few decades, there is no reason to model deep ocean circulation that can take thousands of years to complete a cycle. Not only would adding this data be useless, it would slow down the computer processing time and perhaps give erroneous results by trying to make a connection where none exists. Types of Climate Models ere are several types of climate models, but they can be grouped into four main categories: energy balance models (EBMs); one- dimensional radiative-convective models (RCMs); two-dimensional statistical-dynamical models (SDMs); and three-dimensional general circulation models (GCMs). ese four types increase in complex- ity from rst to fourth, to the degree that they simulate particular processes, and in their temporal and spatial resolution. e simplest models do not allow for much interaction. e most complicated type—the GCM—allows for the most interaction. e type of model used depends on the purpose of the analysis. If a model is run that requires the study of the interaction between physical, chemical, and biological processes, then a more sophisticated model is normally used. EBMs simulate the two most fundamental processes controlling the state of the climate—the global radiation balance and the latitu- dinal (equator to pole) energy transfer. Because EBMs are the most simplistic models, they are usually in a 0-D or 1-D format. In the 0-D form, the Earth is represented as a single point in space. In 1- D models, the dimension that is added is latitude; meaning that at whichever latitude interval is specied, the values in the model (such as albedo, energy ux, or temperature) would be input at each desig- nated latitude. RCMs can be 1-D or 2-D. Height is the attribute that is charac- teristic of these models. With the addition of the z-value, RCMs are able to simulate in detail the transfer of energy through the depth of the atmosphere. ey can simulate the dynamic transformations that [...]... we have about the future of human interactions with the Earth.” error amplification If a compass heading is set even a half degree off, the farther the boat travels, the farther off course it becomes, the error growing in magnitude the longer the boat progresses In large, complex models, such as GCMs, if there is an initial input error—however tiny—in the physics of climate data, as the model runs,... doubling the levels of CO2 in the atmosphere are comparable to a 13 percent increase in water vapor In the Tropics, clouds moisturize the air around them, and clouds are a major source of moisture Lindzen and his researchers focused on cloud cover using the Japanese Geostationary Meteorological Satellite-5 (GMS-5; Japanese name Himawari-5) to collect their measurements The area they focused on was the area... easterlies too weak Modeled subpolar low-pressure systems in the winter tended to be too deep and displaced too far to the east Day-to-day variability tended to be lower than in the real world Finding these discrepancies in models and correcting them are part of the process that enables the creation of stronger models The process is iterative; no model is its strongest after the first run modeLing unCerTainTies... cloud cover He began looking closely at the presence of water vapor as a greenhouse gas and the effect it was having on global warming The warmer the atmosphere becomes, the more water vapor it can hold As the atmosphere absorbs CO2 and the temperature rises, the additional heat allows the atmosphere to absorb even more water vapor The water vapor further enhances the Earth’s greenhouse effect in a progressive... According to the Met Office Hadley Centre, the foremost climate change research center in Britain, the table on page 170 illustrates the climate models they currently use Testing a model—modeling Trouble spots Models are tested at two different levels—at a small scale (did the wind patterns go in the right direction?), which includes the individual parameters; and at a large scale (did the atmosphere... of their effect on global warming in order to be able to model changes associated with their reduction Clouds Because clouds are a smaller-scale phenomena (they are generally smaller than the model’s resolution) and transient—they come and go rather quickly—they are one of the most difficult properties to account for in climate models One thing scientists are struggling with is how   Climate management. .. downstream Then, when entire Practical solutions that Work—getting everyone involved the 20 07 noBel PeaCe Prize The Norwegian Nobel Committee decided that the Nobel Peace Prize for 20 07 was to be shared equally between the Intergovernmental Panel on Climate Change (IPCC) and Albert Gore, Jr., for their efforts to raise awareness and spread knowledge about man-made climate change and to lay the foundation... Nobel Peace Prize for 20 07 to the IPCC and Al Gore, the Norwegian Nobel Committee sought to contribute to a sharper focus on the processes and decisions that are necessary to protect the world’s future, and thereby reduce the threat to the security of mankind Commenting on the award, Gore said, Climate change is a real, rising, imminent, and universal threat to the future of the Earth Our world is spinning... which have their origin within the atmosphere, such as volcanic pollution SDMs are usually 2-D in form—a horizontal and vertical component Currently there are many variations of them These models usually combine the horizontal energy transfer modeled by EBMs with the radiative-convection approach of RCMs GCMs are sets of sophisticated computer programs that simulate the circulation patterns of the Earth’s... model is the ocean counterpart of an AGCM; a three-dimensional representation of oCeAn LAnD surfACe Atmosphere Coupled atmosphereocean model (AoGCm)= AGCm + oGCm regional climate model (rCm) the ocean and sea ice Carbon cycle models: The terrestrial carbon cycle is modeled within the land surface scheme of the AGCM, and the marine carbon cycle within the OGCM Atmospheric chemistry models: Three-dimensional . that knowl- edge explain the climate system’s large-scale features, variability, and 163 Climate Modeling The evolution of climate models beginning in the mid-1 970 s and extending into the near. outcomes. Simplifying the Climate System All models must simplify complex climate systems. One critical aspect of climate models is the detail in which they can reconstruct the part of the world they are. and mathematics. Weather and climate are so complex that without computers it would be impossible to math- ematically quantify the climate system. erefore, up until the com- puter age, there