Further determinations of upper-atmosphere rotational speed from analysis of satellite orbits

The average angular velocity of the upper atmosphere, which we take as Λ times the Earth's angular velocity, can be evaluated by analysing the changes in the orbital inclinations of satellites. In this paper the nine most suitable orbits now available are analysed and values of Λ are found for heights between 200 and 260 km. The results, which are more accurate than in our previous studies, confirm that Λ 1, i.e. that the atmosphere rotates faster than the Earth at these heights, and show that Λ increases with height, from 1.1 at 210 km to 1.4 at 260 km. This corresponds to mean west-to-east winds of 30 m/s at 210 km, increasing to 130 m/s at 260 km height. Results from one satellite indicate that the wind is probably strongest at times near sunset, with Λ = 1.5 ± 0.1 at 200 km height in August 1966. Comparisons are made with previous observational results and some of the suggested theoretical explanations are outlined.     

Validation of the Canadian land surface scheme (class) for a subarctic open woodland

Abstract

This study reports on testing of the peatland version of the Canadian Land Surface Scheme (CLASS) for simulating the energy balance of subarctic open woodland terrain. Model results are compared against several years of measured data from a site near Churchill, Manitoba. In contrast to most forest environments, the floor of the open forest plays a large role in total ecosystem energy exchange. This behaviour presents a significant challenge for land surface models like CLASS and their simplified treatment of vegetation canopies.

Simulations of summer energy balance for seven years encompassing a wide range of meteorological conditions produced consistent results. Root mean square errors for sensible and latent heat fluxes fell between 11 and 28 W m^?2. CLASS consistently underestimated slightly the daily latent heat flux and overestimated the sensible heat flux, average mean bias errors being ‐7.6 and 9.1 W m^?2, respectively. The soil heat flux was less well represented. In general, CLASS was able to capture the diurnal and seasonal behaviour of the measured fluxes under a range of conditions with reasonable accuracy.

In a full year simulation, CLASS reproduced the annual variations in energy balance with some discrepancies associated with snow accumulation and ablation periods. The model performance was sensitive to both snow density and specification of the surface cover. Recommendations for improving the model for subarctic woodlands and terrain types with similar features are discussed.     

Accuracy of a pre-trained sentiment analysis (SA) classification model on tweets related to emergency response and early recovery assessment: the case of 2019 Albanian earthquake

Traditionally, earthquake impact assessments have been made via fieldwork by non-governmental organisations (NGO's) sponsored data collection; however, this approach is time-consuming, expensive and often limited. Recently, social media (SM) has become a valuable tool for quickly collecting large amounts of first-hand data after a disaster and shows great potential for decision-making. Nevertheless, extracting meaningful information from SM is an ongoing area of research. This paper tests the accuracy of the pre-trained sentiment analysis (SA) model developed by the no-code machine learning platform MonkeyLearn using the text data related to the emergency response and early recovery phase of the three major earthquakes that struck Albania on the 26th November 2019. These events caused 51 deaths, 3000 injuries and extensive damage. We obtained 695 tweets with the hashtags: #Albania #AlbanianEarthquake, and #albanianearthquake from the 26th November 2019 to the 3rd February 2020. We used these data to test the accuracy of the pre-trained SA classification model developed by MonkeyLearn to identify polarity in text data. This test explores the feasibility to automate the classification process to extract meaningful information from text data from SM in real-time in the future. We tested the no-code machine learning platform's performance using a confusion matrix. We obtained an overall accuracy (ACC) of 63% and a misclassification rate of 37%. We conclude that the ACC of the unsupervised classification is sufficient for a preliminary assessment, but further research is needed to determine if the accuracy is improved by customising the training model of the machine learning platform.

     

A Complex Filament Evolution

A complex filament composed by a main body a polar filament and a tail—a small filament situated between active regions, was observed between 6 and 14 January 2001. A decaying active region plays the role of attractor for this filament. We have studied the dynamics of the filament which disappeared in a spectacular CME, produced after a helical up-awarded movement of plasma in the filaments loops.     

Use of stream response functions to determine impacts of replacing surface-water use with groundwater withdrawals

A regional-scale numerical groundwater model is used to study the impacts of replacing surface-water use with groundwater wells to improve low-flow stream conditions for endangered species within the Bertrand and Fishtrap watersheds, southern British Columbia, Canada and Washington, USA. Stream response functions ranging from 0 to 1.0 were calculated for individual wells placed within a steady-state groundwater flow model at varying distances from the streams to determine the impact that these replacement wells, operating under sustained pumping rates, would have on summer instream flows. Lower response ratios indicate groundwater pumping will have less of an impact on streamflow than taking an equivalent amount of water directly from a surface-water source. Results show that replacing surface-water use with groundwater withdrawals may be a viable alternative for increasing summer streamflows. Assuming combined response factors should be ≤0.5 for irrigators to undergo the expense of installing new wells, ~57% of the land area within 0.8 km of Bertrand Creek would be suitable for replacement wells. Similarly, 70% of the land area within 0.8 km of Fishtrap Creek was found to be appropriate. A visual analysis tool was developed using STELLA to allow stakeholders to quickly evaluate the impact associated with moving their water right.     

Sodic amphiboles and pyroxenes from fenites in East Africa

During alkali metasomatism of the country-rock associated with ijolite-carbonatite complexes the development of sodic amphibole and/or pyroxene is characteristic. In this paper, some new chemical analyses of these minerals, together with published analyses from fenites of Kenya, Uganda and Tanzania, include those of co-existing pairs of amphibole and pyroxene. The common amphiboles of the fenites are magnesioarfvedsonites with 100 Mg: Mg+Fe+Mn ranging from 67 to 36. They co-exist with aegirines having 0.75 to 0.89 ions Fe⁺³. Most of these minerals are poor in Ca; co-existing pairs tend to show corresponding increases in Ca and in Fe⁺². In the syenitic fenites of Tororo and Budeda, considered to have formed at higher temperatures, the stable mineral is aegirine-augite. New analyses of richterite, magnesioarfvedsonite and aegirine from carbonate-rich rocks are also presented, and the relation between fenites and carbonatites is discussed.