If there was a reduction in uncertainty in scientific research, this would stimulate scientists to carry out new scientific research. Since it is difficult to define uncertainty and it is not even easy to calculate its quantification. But there are also projections. Say no to plagiarism. Get a tailor-made essay on "Why Violent Video Games Shouldn't Be Banned"? Get an original essay Below are the IPCC-ARA's summary climate change projections for the year 2100: There is expected to be an increase The global average temperature at the Earth's surface is between 1.1 and 29 degrees, according to the lowest projection of greenhouse gas emissions in 2100 and there will be a global sea level rise of between 0.18 and 0.38 m. But under the highest emissions scenario it is expected that, due to greenhouse gas emissions, the increase in global temperature will be between 2.4 and 6.4 degrees and the rise in global average sea level will be between 0.26 and 0.59 m. Both of the above projections based on temperature rise and due to the ever lower scenario of greenhouse gas emissions and sea level rise is due to the melting of ice sheets in the northern areas. First, the uncertainty in an increase in temperature and sea level rise can be quantified by two model projections of observing the situation. Second, the range of greenhouse gas emissions shows our knowledge about greenhouse gas emissions due to human activities. The dependence of greenhouse gas emissions depends on a decision that occurs outside the field of physical science. Third, due to sea level rise, there may be uncertainty in a projection as to whether processes that are occurring sparsely in climate models are important and poorly represented or not represented. Finally, Farber's argument discussed above represents a fourth assessment of uncertainty, when he concludes that the IPCC process increases the certainty of climate projections because its completeness and openness reduces the possibility of fundamental errors in conclusions about global warming. This type of judgment by people outside the climate science community is an important indicator of the robustness of knowledge. It asks, with a documented evaluation method, whether non-scientists using the knowledge generated by scientific investigation of the Earth's climate find the information convincing. These distinct shades of uncertainty are just beginning to encompass the spectrum of uncertainty that both scientists and decision makers face. This broader spectrum would include, for example, the erratic and inconsistent expression of uncertainty by scientists. Sources of uncertainty in CMIP5 projections: the recent discussion on the source of uncertainty in IPCC AR5 climate projections (Fig. 11.8, section 11.3.1.1). In which it updates previous analyzes using CMIP3 (temperature, precipitation) to the latest CMIP5 simulations. The main source of uncertainty depends on time, variables and spatial scale. The three main sources of uncertainty in climate projections are future emissions (scenario uncertainty, green), internal climate variability (orange), and model differences (blue). Internal variability is more or less constant over time. And other uncertainties grow with time. But at different paces. Although there is no perfect way to clearly separate these uncertainties. And different methods gave similar results. Overall the discussion on CMIP5 has not changed much compared to CMIP3. For global temperature, the spread between RCP scenarios is the.