The world is changing towards using more renewable, rather than fossil energy sources in order to reach the 1.5 degrees celsius goal of the Paris agreement (Merchant, 2018). This thesis’ main focus is to investigate the solar irradiance in Tromsø using 2-axis tracking measurements from May 2020. The reduction of global irradiance and direct irradiance is also compared against the values of the other ...

Radar remote sensing is a key technology for monitoring sea ice. In this regard, passive microwave and Synthetic Aperture Radars (SARs) are the most important sensor types. This technology has been used for sea ice applications for four decades, but there are still many uncertainties related to sea ice monitoring by SAR. Some of these may be solved by multi-sensor observations, in which case other ...

Renewable means of energy production have recently become cost competitive with fossil fuels. However, before they can be completely phased out, the issue of storing renewable energy must be addressed. Two energy storage technologies that have gotten a lot of attention over the past years are lithium ion batteries and hydrogen energy storage. Each of these technologies have their advantages, ...

Anthropogenic emission of greenhouse gases is causing an unbalance in the Earth’s climate system, leading to global climate change. The implications of these changes are dramatic, with a need for a global-scale assessment. The remaining carbon budget (RCB) is a measure of the amount of greenhouse gasses (GHGs) that can be emitted if we are to reach a specific temperature target. Traditionally, carbon ...

We are changing the global climate by altering the Earths energy balance through the emission of greenhouse gasses. The international community aims to prevent dangerous warming with mitigative efforts. A remaining carbon budget (RCB) can roughly quantify an allowable amount of emissions for keeping the temperature below a set target. We have built a simple climate model using impulse response ...

The aim of this study is to investigate how sputtering by impacting solar wind particles influence the lifetime of dust particles in the inner heliosphere near the Sun.<p><p> We consider three typical dust materials: silicate, Fe_0.4Mg_0.6O and carbon and describe their sputtering yields based on atomic yields given by the Stopping and Range of Ions in Matter (SRIM) package. ...

The machine-learning research community has focused greatly on bias in algorithms and have identified different manifestations of it. Bias in training samples is recognised as a potential source of prejudice in machine learning. It can be introduced by the human experts who define the training sets. As machine-learning techniques are being applied to auroral classification, it is important to identify ...

The ice sheet model intercomparison project for CMIP6 (ISMIP6) effort brings together the ice sheet and climate modeling communities to gain understanding of the ice sheet contribution to sea level rise. ISMIP6 conducts stand-alone ice sheet experiments that use space- and time-varying forcing derived from atmosphere–ocean coupled global climate models (AOGCMs) to reflect plausible trajectories for ...

Snow avalanches threaten human lives, settlements and roads in snow covered mountainous areas. For avalanche forecasting, knowledge of the spatio-temporal occurrence of avalanche activity is critical. Automatic avalanche detection algorithms have been developed to enable consistent avalanche activity monitoring for large regions. The Satskred avalanche detection algorithm developed by NORCE applies ...

We propose a deep-learning framework to detect and categorize oil spills in synthetic aperture radar (SAR) images at a large scale. Through a carefully designed neural network model for image segmentation trained on an extensive dataset, we obtain state-of-the-art performance in oil spill detection, achieving results that are comparable to results produced by human operators. We also introduce a ...