Land surface temperature (LST) serves as an important climate variable which is relevant to a number of studies related to energy and water exchanges, vegetation growth and urban heat island effects. Although LST can be derived from satellite observations, these approaches rely on cloud‐free acquisitions. This represents a significant obstacle in regions which are prone to cloud cover. In this ...

This paper presents a robust method combining electron temperatures and density to identify the winter dayside auroral region in Incoherent Scatter Radar (ISR) observations. In literature, a common proxy for identifying the dayside auroral region has been enhanced electron temperatures T_e at high altitudes. However, T_e is intimately related to N_e and their ...

Zero-shot learning (ZSL) is a machine learning paradigm that enables models to recognize and classify data from classes they have not encountered during training. This approach is particularly advantageous in recognizing activities where labeled data is limited, allowing models to identify new, unseen activities by leveraging semantic knowledge from seen activities. In this paper, we explore the ...

Sea ice is a key element of the global Earth system, with a major impact on global climate and regional weather. Unfortunately, accurate sea ice modeling is challenging due to the diversity and complexity of underlying physics happening there, and a relative lack of ground truth observations. This is especially true for the Marginal Ice Zone (MIZ), which is the area where sea ice is affected by ...

Observations and present knowledge of heavy ions with mass ≥ 27 in the magnetosphere are reviewed. There are four ultimate sources of these heavy ions: the solar wind (mainly high charge-state atomic ions), the ionosphere (mainly molecular ions), the atmospheric metal layers that originate ultimately from ablation of meteoroids and possibly space debris (low charge-state metallic ions and metal-rich ...

Deep Neural networks has pushed the boundary for what is achievable in the field of machine learning. At its core the Neural network maps data from an input space, to a highly abstract latent space. The representations of these latent mappings are critical for the neural networks ability to perform the task it is given. However critical, our knowledge on these abstract representations in the latent ...

Baffin Bay is located between Greenland and several islands of the Canadian Arctic, providing a conduit for the downstream transport of ice and freshwater to the North Atlantic via Davis Strait. Using satellite observations from Sentinel‐1, the RADARSAT Constellation Mission, and CryoSat‐2, we estimated the sea ice export through Davis Strait and winter ice production in Baffin Bay from 2016 to ...

To viktige prinsipper for å øke studentenes læring i undervisning er aktiv deltagelse og formativ vurdering. Innføring av disse prinsippene i undervisning med store studentgrupper kan imidlertid by på utfordringer, særlig i nettbasert undervisning. En mulig løsning kan være bruk av flervalgsoppgaver som diagnostisk testing med innsamling av svarene og påfølgende formativ vurdering – en undervisningsform ...

Precise measurements of Arctic sea ice mass balance are necessary to understand the rapidly changing sea ice cover and its representation in climate models. During the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition, we made repeat point measurements of snow and ice thickness on primarily level first- and second-year ice (FYI, SYI) using ablation stakes and ...

Polar mesospheric summer echoes (PMSEs) are radar echoes that are measured in the upper atmosphere during the summer months and that can occur in several layers. In this study, we aimed to investigate the relationship between PMSE layers ranging from 80 to 90 km altitude and the solar cycle. We investigated 230 h of observations from the EISCAT very high frequency (VHF) radar located near Tromsø, ...