Climate change feedback | EPFL Graph Search

Are you an EPFL student looking for a semester project?

Work with us on data science and visualisation projects, and deploy your project as an app on top of GraphSearch.

Climate change feedbacks are effects of global warming that amplify or diminish the effect of forces that initially cause the warming. Positive feedbacks enhance global warming while negative feedbacks weaken it. Feedbacks are important in the understanding of climate change because they play an important part in determining the sensitivity of the climate to warming forces. Climate forcings and feedbacks together determine how much and how fast the climate changes. Large positive feedbacks can lead to tipping points—abrupt or irreversible changes in the climate system—depending upon the rate and magnitude of the climate change. The main positive feedback in global warming is the tendency of warming to increase the amount of water vapor in the atmosphere, which in turn leads to further warming. Positive climate feedbacks include the carbon cycle positive feedbacks which include arctic methane release from thawing permafrost peat bogs and hydrates, abrupt increases in atmospheric methane, decomposition, peat decomposition, rainforest drying, forest fires, desertification. Other positive climate feedbacks include cloud feedback, ice–albedo feedback and gas release. With regards to negative climate feedbacks, they can be listed as follows: Carbon cycle negative feedbacks (role of oceans, chemical weathering, primary production through photosynthesis) and blackbody radiation. The main negative feedback or "cooling response" comes from the Stefan–Boltzmann law, the amount of heat radiated from the Earth into space changes with the fourth power of the temperature of Earth's surface and atmosphere. However, it is typically not considered a feedback. Observations and modeling studies indicate that globally the positive feedbacks outweigh the negative feedbacks, indicating a net positive feedback to warming. Climate systempositive feedback and negative feedback In climate science, a feedback that amplifies an initial warming is called a positive feedback. On the other hand, a feedback that reduces an initial warming is called a negative feedback.

About this result

This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.

Related publications (2)

Related people (2)

Related units (1)

Related concepts (32)

Related courses (11)

Related lectures (186)

Related MOOCs (3)

ENV-410: Science of climate change

The course equips students with a comprehensive scientific understanding of climate change covering a wide range of topics from physical principles, historical climate change, greenhouse gas emissions

CS-401: Applied data analysis

This course teaches the basic techniques, methodologies, and practical skills required to draw meaningful insights from a variety of data, with the help of the most acclaimed software tools in the dat

HUM-121(b): Global issues: climate B

Le cours présente les enjeux mondiaux liés au climat: système climatique et prévisions ; impacts sur écosystèmes et biodiversité ; cadrage historique et débat public ; objectifs et politiques climatiq

A building is designed for one set of typical climatic conditions. In the context of expected climate change, substantial numbers of existing and new buildings are expected to survive long enough to experience perceptible shifts in climate ‘normals’ (averages). This is problematic for predicting building performance, largely because the exact nature of climate change is hard to predict with certainty. Thus an optimal design is not only tuned to the original design conditions, but is also robust to changes in climatic conditions in the sense of a low sensitivity of its performance. To predict a building’s response to changes in typical weather, two inputs are required: weather data representing this change, and suitable metrics to compare building performance across different climate normals. This report presents initial work on a proposed method for assessing the sensitivity of new or existing buildings to climate change. This method begins with a selection of weather files to represent climate change, then quantifies a building’s passive performance in those climates using an enthalpy-based metric, and ends with a graphical analysis of the performance of the building in different climates to assess its robustness. In this report, we propose an objective performance metric based on the extent to which a building creates indoor conditions passively, i.e. without auxiliary systems. Initial work suggests that the performance assessment carried out here is reproducible and applicable for indoor environment design and evaluation in different ranges of climate change. This approach enables a comparison of building performance without the bias introduced by inherent differences in climatic conditions.

2013

Evaluation and extension of an automated system to diagnose the health of premature babies

Camille Joggi

Premature babies are not fully equipped to deal with the outside world. Their immature bodies make them highly at risk to a large number of physiological complications. Therefore, while they are still immature, premature babies are taken care of in neonatology intensive care units, where they are kept in a controlled and protective environment. In these units, the babies' vital parameters, such as their heart rate and temperature, are tightly monitored. The devices used to record this data are fitted with alarms that are triggered automatically when something wrong is detected. However, the alarm systems currently used are often unable to discriminate between real physiological problems and artefacts that should be ignored (e.g. when a measurement device drops-out). As a result, these systems produce a high rate of false alarms, where the alarm is triggered when nothing is clinically wrong. The can have unwanted consequences: first, it creates a noisy environment, which may disturb the babies; second, it can lead to the alarm being ignored when there is actually something wrong. In order to address this problem, my host laboratory has constructed a system that can automatically infer the state of health of premature babies in neonatology units, based on their recorded physiological data. The new system is designed to be able to deal with artefactual changes in the measurements, hopefully resulting in a reduced number of false alarms. In this thesis, I describe my contribution to this project, which is twofold. The first part deals with the problem of evaluating the performance of the system. To do this, I developed an online feedback process, where clinicians could provide information about the true clinical interpretation of the physiological data, which could be compared to the output of the system. The feedbacks provided by the clinicians were then analysed to investigate how the system could be improved. The second part of my thesis was motivated be early feedbacks from the clinicians, which indicated that the system was unable to deal with changes in the humidity measurements that occurred when the incubator door was opened and closed. To address this, I extended the current system, so that it was able to account for these changes, thereby increasing its capability to detect "true" physiological problems during the period after the incubator door is closed.

2011

Deforestation and climate change

Deforestation is a primary contributor to climate change, and climate change affects forests. Land use changes, especially in the form of deforestation, are the second largest anthropogenic source of atmospheric carbon dioxide emissions, after fossil fuel combustion. Greenhouse gases are emitted during combustion of forest biomass and decomposition of remaining plant material and soil carbon. Global models and national greenhouse gas inventories give similar results for deforestation emissions.

Climate change feedback

Ice–albedo feedback

Ice–albedo feedback is a positive feedback climate process where a change in the area of ice caps, glaciers, and sea ice alters the albedo and surface temperature of a planet. Ice is very reflective, therefore it reflects far more solar energy back to space than the other types of land area or open water. Ice–albedo feedback plays an important role in global climate change. For instance, at higher latitudes, warmer temperatures melt the ice sheets.

Global Arctic

The Global Arctic MOOC introduces you the dynamics between global changes and changes in the Arctic. This course aims to highlight the effects of climate change in the Polar region. In turn, it will u

Teaching Science and Engineering

This MOOC is designed to help doctoral teaching assistants develop their teaching skills in scientific and engineering disciplines at university level. The MOOC will address what to do when you teach

Foundations in Science and Engineering Teaching, Learning, and Assessment

This MOOC is designed to help doctoral teaching assistants develop their teaching skills in scientific and engineering disciplines at university level. The MOOC will address what to do when you teach

Probability Distributions in Environmental Studies ENV-400: Air pollution and climate change

Explores probability distributions for random variables in air pollution and climate change studies, covering descriptive and inferential statistics.

Snow Physics and Hydrology ENV-525: Physics and hydrology of snow

Covers snow physics, hydrology, modeling, and climate impact, emphasizing self-learning and practical understanding.

Radiative Forcing & Climate Sensitivity ENV-410: Science of climate change

Explores radiative forcing, climate sensitivity, and feedback mechanisms in climate change, emphasizing the role of various components like CO2 and methane.