Browsing by Subject "WEATHER"

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  • Linek, Nils; Brzek, Pawel; Gienapp, Phillip; O'Mara, M. Teague; Pokrovsky, Ivan; Schmidt, Andreas; Shipley, J. Ryan; Taylor, Jan R. E.; Tiainen, Juha; Volkmer, Tamara; Wikelski, Martin; Partecke, Jesko (2021)
    Background Many birds species range over vast geographic regions and migrate seasonally between their breeding and overwintering sites. Deciding when to depart for migration is one of the most consequential life-history decisions an individual may make. However, it is still not fully understood which environmental cues are used to time the onset of migration and to what extent their relative importance differs across a range of migratory strategies. We focus on departure decisions of a songbird, the Eurasian blackbird Turdus merula, in which selected Russian and Polish populations are full migrants which travel relatively long-distances, whereas Finnish and German populations exhibit partial migration with shorter migration distances. Methods We used telemetry data from the four populations (610 individuals) to determine which environmental cues individuals from each population use to initiate their autumn migration. Results When departing, individuals in all populations selected nights with high atmospheric pressure and minimal cloud cover. Fully migratory populations departed earlier in autumn, at longer day length, at higher ambient temperatures, and during nights with higher relative atmospheric pressure and more supportive winds than partial migrants; however, they did not depart in higher synchrony. Thus, while all studied populations used the same environmental cues, they used population-specific and locally tuned thresholds to determine the day of departure. Conclusions Our data support the idea that migratory timing is controlled by general, species-wide mechanisms, but fine-tuned thresholds in response to local conditions.
  • Korhonen, Natalia; Hyvärinen, Otto; Kämäräinen, Matti; Richardson, David S.; Järvinen, Heikki; Gregow, Hilppa (2020)
    The strength of the stratospheric polar vortex influences the surface weather in the Northern Hemisphere in winter; a weaker (stronger) than average stratospheric polar vortex is connected to negative (positive) Arctic Oscillation (AO) and colder (warmer) than average surface temperatures in northern Europe within weeks or months. This holds the potential for forecasting in that timescale. We investigate here if the strength of the stratospheric polar vortex at the start of the forecast could be used to improve the extended-range temperature forecasts of the European Centre for Medium-Range Weather Forecasts (ECMWF) and to find periods with higher prediction skill scores. For this, we developed a stratospheric wind indicator (SWI) based on the strength of the stratospheric polar vortex and the phase of the AO during the following weeks. We demonstrate that there was a statistically significant difference in the observed surface temperature in northern Europe within the 3-6 weeks, depending on the SWI at the start of the forecast. When our new SWI was applied in post-processing the ECMWF's 2-week mean temperature reforecasts for weeks 3-4 and 5-6 in northern Europe during boreal winter, the skill scores of those weeks were slightly improved. This indicates there is some room for improving the extended-range forecasts, if the stratosphere-troposphere links were better captured in the modelling. In addition to this, we found that during the boreal winter, in cases where the polar vortex was weak at the start of the forecast, the mean skill scores of the 3-6 weeks' surface temperature forecasts were higher than average.
  • Esau, Igor; Bobylev, Leonid; Donchenko, Vladislav; Gnatiuk, Natalia; Lappalainen, Hanna K.; Konstantinov, Pavel; Kulmala, Markku; Mahura, Alexander; Makkonen, Risto; Manvelova, Alexandra; Miles, Victoria; Petaja, Tuukka; Poutanen, Pyry; Fedorov, Roman; Varentsov, Mikhail; Wolf, Tobias; Zilitinkevich, Sergej; Baklanov, Alexer (2021)
    Sustaining urban environmental quality requires effective policy measures that integrate local monitoring and contextualized high-resolution modelling with actionable scenarios. Knowledgeable decision making in this field can nowadays be supported by an array of atmospheric models, but their transfer into an Integrated Urban hydrometeorological, climate and environmental Services (IUS) remains challenging. Methodological aspects that are beyond pure technicalities of the model-to-model coupling are still poorly explored. Modeling downscaling chains lack their most user-relevant link - urban-to-neighborhood scale observations and models. This study looks at a socio-environmental context of the high-resolution atmospheric modeling in the case study of the Arctic urban cluster of Apatity and Kirovsk, Russia. We demonstrate that atmospheric dynamics of the lowermost, turbulent air layers is highly localized during the most influential episodes of atmospheric pollution. Urban micro-climates create strong circulations (winds) that are sensitive to the local environmental context. As the small-scale turbulence dynamics is not spatially resolved in meteorological downscaling or statistical modeling, capturing this local context requires specialized turbulence-resolving (large-eddy simulation) models. Societal acceptance of the urban modeling could be increased in the IUS with horizontally integrated modeling driven by localized scenarios. This study presents an enhanced integrated approach, which incorporates a large-eddy simulation model PALM into meteorological downscaling chains of a climate model (EC-EARTH), a numerical weather prediction - atmospheric chemical transport model (ENVIRO-HIRLAM) and a regional-scale meteorological model (COSMO-CLM). We discuss how this approach could be further developed into an environmental component of a digital "smart city".
  • Bradter, Ute; Johnston, Alison; Hochachka, Wesley M.; Soultan, Alaaeldin; Brommer, Jon E.; Gaget, Elie; Kalas, John Atle; Lehikoinen, Aleksi; Lindstrom, Ake; Piirainen, Sirke; Pavon-Jordan, Diego; Part, Tomas; Oien, Ingar Jostein; Sandercock, Brett K. (2022)
    The relationships between species abundance or occurrence versus spatial variation in climate are commonly used in species distribution models to forecast future distributions. Under "space-for-time substitution", the effects of climate variation on species are assumed to be equivalent in both space and time. Two unresolved issues of space-for-time substitution are the time period for species' responses and also the relative contributions of rapid- versus slow reactions in shaping spatial and temporal responses to climate change. To test the assumption of equivalence, we used a new approach of climate decomposition to separate variation in temperature and precipitation in Fennoscandia into spatial, temporal, and spatiotemporal components over a 23-year period (1996-2018). We compiled information on land cover, topography, and six components of climate for 1756 fixed route surveys, and we modeled annual counts of 39 bird species breeding in the mountains of Fennoscandia. Local abundance of breeding birds was associated with the spatial components of climate as expected, but the temporal and spatiotemporal climatic variation from the current and previous breeding seasons were also important. The directions of the effects of the three climate components differed within and among species, suggesting that species can respond both rapidly and slowly to climate variation and that the responses represent different ecological processes. Thus, the assumption of equivalent species' response to spatial and temporal variation in climate was seldom met in our study system. Consequently, for the majority of our species, space-for-time substitution may only be applicable once the slow species' responses to a changing climate have occurred, whereas forecasts for the near future need to accommodate the temporal components of climate variation. However, appropriate forecast horizons for space-for-time substitution are rarely considered and may be difficult to reliably identify. Accurately predicting change is challenging because multiple ecological processes affect species distributions at different temporal scales.
  • Petäjä, T.; Järvi, L.; Kerminen, V. -M.; Ding, A. J.; Sun, J. N.; Nie, W.; Kujansuu, J.; Virkkula, A.; Yang, X. -Q.; Fu, C. B.; Zilitinkevich, S.; Kulmala, M. (2016)
    Severe air pollution episodes have been frequent in China during the recent years. While high emissions are the primary reason for increasing pollutant concentrations, the ultimate cause for the most severe pollution episodes has remained unclear. Here we show that a high concentration of particulate matter (PM) will enhance the stability of an urban boundary layer, which in turn decreases the boundary layer height and consequently cause further increases in PM concentrations. We estimate the strength of this positive feedback mechanism by combining a new theoretical framework with ambient observations. We show that the feedback remains moderate at fine PM concentrations lower than about 200 mu g m(-3), but that it becomes increasingly effective at higher PM loadings resulting from the combined effect of high surface PM emissions and massive secondary PM production within the boundary layer. Our analysis explains why air pollution episodes are particularly serious and severe in megacities and during the days when synoptic weather conditions stay constant.
  • Marke, Tobias; Crewell, Susanne; Schemann, Vera; Schween, Jan H.; Tuononen, Minttu (2018)
    Low-level-jet (LLJ) periods are investigated by exploiting a long-termrecord of ground-based remote sensing Doppler wind lidar measurements supported by tower observations and surface flux measurements at the Julich Observatory for Cloud Evolution (JOYCE), a midlatitude site in western Germany. LLJs were found 13% of the time during continuous observations over more than 4 yr. The climatological behavior of the LLJs shows a prevailing nighttime appearance of the jets, with a median height of 375 m and a median wind speed of 8.8 ms(-1) at the jet nose. Significant turbulence below the jet nose only occurs for high bulk wind shear, which is an important parameter for describing the turbulent characteristics of the jets. The numerous LLJs (16% of all jets) in the range of wind-turbine rotor heights below 200 m demonstrate the importance of LLJs and the associated intermittent turbulence for wind-energy applications. Also, a decrease in surface fluxes and an accumulation of carbon dioxide are observed if LLJs are present. A comprehensive analysis of an LLJ case shows the influence of the surrounding topography, dominated by an open pit mine and a 200-m-high hill, on the wind observed at JOYCE. High-resolution large-eddy simulations that complement the observations show that the spatial distribution of the wind field exhibits variations connected with the orographic flow depending on the wind direction, causing high variability in the long-term measurements of the vertical velocity.
  • Asvestari, Eleanna; Pomoell, Jens; Kilpua, Emilia; Good, Simon; Chatzistergos, Theodosios; Temmer, Manuela; Palmerio, Erika; Poedts, Stefaan; Magdalenic, Jasmina (2021)
    Context. Coronal mass ejections (CMEs) are a manifestation of the Sun's eruptive nature. They can have a great impact on Earth, but also on human activity in space and on the ground. Therefore, modelling their evolution as they propagate through interplanetary space is essential. Aims. EUropean Heliospheric FORecasting Information Asset (EUHFORIA) is a data-driven, physics-based model, tracing the evolution of CMEs through background solar wind conditions. It employs a spheromak flux rope, which provides it with the advantage of reconstructing the internal magnetic field configuration of CMEs. This is something that is not included in the simpler cone CME model used so far for space weather forecasting. This work aims at assessing the spheromak CME model included in EUHFORIA. Methods. We employed the spheromak CME model to reconstruct a well observed CME and compare model output to in situ observations. We focus on an eruption from 6 January 2013 that was encountered by two radially aligned spacecraft, Venus Express and STEREO-A. We first analysed the observed properties of the source of this CME eruption and we extracted the CME properties as it lifted off from the Sun. Using this information, we set up EUHFORIA runs to model the event. Results. The model predicts arrival times from half to a full day ahead of the in situ observed ones, but within errors established from similar studies. In the modelling domain, the CME appears to be propagating primarily southward, which is in accordance with white-light images of the CME eruption close to the Sun. Conclusions. In order to get the observed magnetic field topology, we aimed at selecting a spheromak rotation angle for which the axis of symmetry of the spheromak is perpendicular to the direction of the polarity inversion line (PIL). The modelled magnetic field profiles, their amplitude, arrival times, and sheath region length are all affected by the choice of radius of the modelled spheromak.
  • Landauer, Mia; Goodsite, Michael Evan; Juhola, Sirkku (2018)
    The tourism sector is affected by climate change. Nordic tourism destinations have also experienced changes, such as changing precipitation patterns, lack of snow in winter and shifts in seasons. The sector has to implement adaptation strategies but it is unclear whether the current public climate policy is sufficient to support considering adaptation actions. We reviewed national climate strategies of the Nordic countries from the perspectives of tourism, but excluding the transport sector. We also reviewed Nordic national tourism strategies from the perspective of climate change, particularly the extent to which they address climate adaptation. We found out that the national climate strategies do not pay enough attention to tourism adaptation needs, nor do the national tourism strategies present adaptation actions that tourism actors could consider. To connect these national-level strategies, there is a need to review adaptation actions for tourism within the national adaptation framework supported by research based evidence. Next, by means of Nordic cooperation, guidance for both public and private tourism actors within and across Nordic countries can be provided. This can enhance the competitiveness and resilience of the Nordic tourism supply and contribute to the development of economically, environmentally and socially sustainable tourism in the region.
  • Lehikoinen, Aleksi; Linden, Andreas; Karlsson, Mans; Andersson, Arne; Crewe, Tara L.; Dunn, Erica H.; Gregory, George; Karlsson, Lennart; Kristiansen, Vidar; Mackenzie, Stuart; Newman, Steve; Roer, Jan Erik; Sharpe, Chris; Sokolov, Leonid V.; Steinholtz, Asa; Stervander, Martin; Tirri, Ina-Sabrina; Tjornlov, Rune Skjold (2019)
    Climate change has been shown to shift the seasonal timing (i.e. phenology) and distribution of species. The phenological effects of climate change on living organisms have often been tested using first occurrence dates, which may be uninformative and biased. More rarely investigated is how different phases of a phenological sequence (e.g. beginning, central tendency and end) or its duration have changed over time. This type of analysis requires continuous observation throughout the phenological event over multiple years, and such data sets are rare. In this study we examined the impact of temperature on long-term change of passage timing and duration of the spring migration period in birds, and which species' traits explain species-specific variation. Data used covered 195 species from 21 European and Canadian bird observatories from which systematic daily sampling protocols were available. Migration dates were negatively associated with early spring temperature and timings had in general advanced in 57 years. Short-distance migrants advanced the beginning of their migration more than long-distance migrants when corrected for phylogenic relatedness, but such a difference was not found in other phases of migration. The advancement of migration has generally been greater for the beginning and median phases of migration relative to the end, leading to extended spring migration seasons. Duration of the migration season increased with increasing temperature. Phenological changes have also been less noticeable in Canada even when corrected for rate of change in temperature. To visualize long-term changes in phenology, we constructed the first multi-species spring migration phenology indicator to describe general changes in median migration dates in the northern hemisphere. The indicator showed an average advancement of one week during five decades across the continents (period 1959-2015). The indicator is easy to update with new data and we therefore encourage future research to investigate whether the trend towards longer periods of occurrence or emergence in spring is also evident in other migratory populations. Such phenological changes may influence detectability in monitoring schemes, and may have broader implications on population and community dynamics.
  • Seitola, Teija; Silen, Johan; Järvinen, Heikki (2015)
    In this article, we introduce a new algorithm called randomised multichannel singular spectrum analysis (RMSSA), which is a generalisation of the traditional multichannel singular spectrum analysis (MSSA) into problems of arbitrarily large dimension. RMSSA consists of (1) a dimension reduction of the original data via random projections, (2) the standard MSSA step and (3) a recovery of the MSSA eigenmodes from the reduced space back to the original space. The RMSSA algorithm is presented in detail and additionally we show how to integrate it with a significance test based on a red noise null-hypothesis by Monte-Carlo simulation. Finally, RMSSA is applied to decompose the 20th century global monthly mean near-surface temperature variability into its low-frequency components. The decomposition of a reanalysis data set and two climate model simulations reveals, for instance, that the 2-6 yr variability centred in the Pacific Ocean is captured by all the data sets with some differences in statistical significance and spatial patterns.
  • Hautsalo, Juho; Jauhiainen, Lauri; Hannukkala, Asko; Manninen, Outi; Vetelainen, Merja; Pietila, Leena; Peltoniemi, Kirsi; Jalli, Marja (2020)
    Fusarium head blight (FHB) and the mycotoxins produced by its causal agents in oats (Avena sativaL.) have become a growing problem in northern countries over the last decades. The development of resistant cultivars would offer a highly needed and economical solution to the problem. To tackle the high genotypexenvironment interaction of FHB, a combined analysis was carried out on eight greenhouse and 13 field experiments inoculated with DON-producingFusariumspecies. Our data included 406 oat genotypes consisting of Nordic cultivars, breeding lines and potentially resistant gene bank accessions. High variation in the DON accumulation estimates in the material shows that the selection of genotypes with better resistance would be valuable. The greenhouse and field studies resulted in significantly different oat genotype susceptibility rankings for both DON andFusariuminfected kernels. The results obtained from the field experiments have more practical relevance for farmers and breeders for the identification of DON resistant cultivars than greenhouse screenings. Days to maturity and the plant height of the genotypes both significantly affected theFusariuminfections and DON in the field. The relationship betweenFusariuminfected kernels, DONand germination capacity provide an insight into the composition of genotypes with resistance. The core set of 30 oat genotypes, which were phenotyped in several experiments, provides valuable examples of both highly susceptible and moderately resistant oat genotypes.
  • Luomaranta, Anna M; Aalto, Juha; Jylhä, Kirsti (2019)
    Snow conditions in high-latitude regions are changing in response to climate warming, and these changes are likely to accelerate as the warming proceeds. Here, we analyse daily gridded snow depth, temperature and precipitation data from Finland over the period 1961-2014 to discover the ongoing changes in monthly average snow depths (SN) and several snow-related indices. Our results indicate that regional differences of changes in snow conditions can be relatively large, even within such a small district as Finland. Moreover, the interannual variation of the various snow indices was found to be larger in southern Finland than in northern Finland. The largest decrease in snow depth occurred in the southern, western and central parts of Finland in late winter and early spring. This decrease was driven by increasing mixed and liquid precipitation and, especially in spring, increasing temperature. In northern Finland, the decreasing trend of snow depth was most evident in spring, but no change occurred during winter months, although the amount of solid precipitation was found to increase in December-February. In the same months, temperature and the amount of mixed and liquid precipitation increased, likely counteracting the effects of the increasing solid precipitation on snow depth. The annual maximum snow depth that typically occurs in March was found to decrease in over 85% of Finland's area, most strongly in western coastal areas. In almost half of Finland's area, this decrease occurred despite increasing solid precipitation. Our findings highlight the complexity of the responses of snow conditions to climatic variability in northern Europe.
  • Deshpande, Purabi; Lehikoinen, Petteri; Thorogood, Rose; Lehikoinen, Aleksi (2022)
    Aim Abundances of animals vary according to species-specific habitat selection, but habitats are undergoing rapid change in response to anthropogenic alterations of land use and climate. The long-term decline of snowfall is one of the most dramatic abiotic changes in boreal regions, with potential to alter species communities and shape future ecosystems. However, the effects of snow cover on habitat-specific abundances remain unclear for many taxa. Here we explore whether long-term declines in snow cover affect the abundances of overwintering birds. Taxon Fifty bird species. Location Finland, Northern Europe. Methods We used generalized linear mixed models to analyse citizen-led monitoring data from 196 transects over a 32-year period to assess whether abundances of birds have changed in built-up areas, farmlands and forests, and whether these covary with warming temperatures and decreasing snow. We then explored if changes in abundance can be explained by body mass, migration strategy or feeding guilds of the species. Results Over the study period, the abundance of overwintering birds increased. This increase was most pronounced in farmlands (69.6%), where abundances were positively associated with decreasing snow depth. On the other hand, while abundances in built-up habitats (19.5%) decreased over the study period, they increased in periods of high snow depths. Finally, we found that the short-distance migration strategy explains changes in bird abundances with snow. In farmlands, ground feeding birds and heavier birds also show a positive trends in abundance with decreasing snow depths. Main conclusions Local snow conditions are driving habitat selection of birds in the winter; birds in farmlands were most responsive to a decrease in snow depth. Changing snow depths can affect bird movements across habitats in the winter, but also influence migratory patterns and range shifts of species.
  • Kämäräinen, Matti; Uotila, Petteri; Karpechko, Alexey; Hyvärinen, Otto; Lehtonen, Ilari; Räisänen, Jouni (2019)
    A statistical learning approach to produce seasonal temperature forecasts in western Europe and Scandinavia was implemented and tested. The leading principal components (PCs) of sea surface temperature (SST) and the geopotential at the 150-hPa level (GPT) were derived from reanalysis datasets and used at different lags (from one to five seasons) as predictors. Random sampling of both the fitting years and the potential predictors together with the Least Absolute Shrinkage and Selection Operator regression (LASSO) was used to create a large ensemble of statistical models. Applying the models to independent test years shows that the ensemble performs well over the target areas and that the ensemble mean is more accurate than the best individual ensemble member on average. Skillful results were especially found for summer and fall, with the anomaly correlation coefficient values ranging between 0.41 and 0.68 for these seasons. The correct simulation of decadal trends, using sufficiently long time series for fitting (70 years), and the use of lagged predictors increased the prediction skill. The decadal-scale variability of SST, most importantly the Atlantic multidecadal oscillation (AMO), and different PCs of GPT are the most important individual predictors among all predictors. Both SST and GPT bring equally much predictive power, although their importance is different in different seasons.
  • Jonauskaite, Domicele; Abdel-Khalek, Ahmed; Abu-Akel, Ahmad; Al-Rasheed, Abdulrahman Saud; Antonietti, Jean-Philippe; Ásgeirsson, Árni Gunnar; Atitsogbe, Kokou Amenyona; Barma, Marodégueba; Barratt, Daniel; Bogushevskaya, Victoria; Bouayed Meziane, Maliha Khadidja; Chamseddine, Amer; Charernboom, Thammanard; Chkonia, Eka; Ciobanu, Teofil; Corona, Violeta; Creed, Allison; Dael, Nele; Daouk, Hassan; Dimitrova, Nevena; Doorenbos, Cornelis B.; Fomins, Sergejs; Fonseca-Pedrero, Eduardo; Gaspar, Augusta; Gizdic, Alena; Griber, Yulia A.; Grimshaw, Gina; Hasan Aya, Ahmed; Havelka, Jelena; Hirnstein, Marco; Karlsson, Bodil S.A.; Kim, Jejoong; Konstantinou, Nikos; Laurent, Eric; Lindeman, Marjaana; Manav, Banu; Marquardt, Lynn; Mefoh, Philip; Mroczko-Wąsowicz, Aleksandra; Mutandwa, Phillip; Muthusi, Steve; Ngabolo, Georgette; Oberfeld, Daniel; Papadatou-Pastou, Marietta; Perchtold, Corinna M.; Pérez-Albéniz, Alicia; Pouyan, Niloufar; Rashid Soron, Tanjir; Roinishvili, Maya; Romanyuk, Lyudmyla; Salgado Montejo, Alejandro; Sultanova, Aygun; Tau, Ramiro; Uusküla, Mari; Vainio, Suvi; Vargas-Soto, Veronica; Volkan, Eliz; Wąsowicz, Grażyna; Zdravković, Sunčica; Zhang, Meng; Mohr, Christine (2019)
    Across cultures, people associate colours with emotions. Here, we test the hypothesis that one driver of this cross-modal correspondence is the physical environment we live in. We focus on a prime example – the association of yellow with joy, – which conceivably arises because yellow is reminiscent of life-sustaining sunshine and pleasant weather. If so, this association should be especially strong in countries where sunny weather is a rare occurrence. We analysed yellow-joy associations of 6625 participants from 55 countries to investigate how yellow-joy associations varied geographically, climatologically, and seasonally. We assessed the distance to the equator, sunshine, precipitation, and daytime hours. Consistent with our hypotheses, participants who live further away from the equator and in rainier countries are more likely to associate yellow with joy. We did not find associations with seasonal variations. Our findings support a role for the physical environment in shaping the affective meaning of colour.
  • Ruosteenoja, Kimmo; Markkanen, Tiina; Räisänen, Jouni (2020)
    Global warming acts to prolong thermal summers and shorten winters. In this work, future changes in the lengths and timing of four thermal seasons in northern Europe, with threshold temperatures 0 and 10 degrees C, are derived from bias-adjusted output data from 23 CMIP5 global climate models. Three future periods and two Representative Concentration Pathway (RCP) scenarios are discussed. The focus is on the period 2040-2069 under RCP4.5, which approximately corresponds to a 2 degrees C global warming relative to the preindustrial era. By the period 2040-2069, the average length of the thermal summer increases by nearly 30 days relative to 1971-2000, and the thermal winter shortens by 30-60 days. The timing of the thermal springs advances while autumns delay. Within the model ensemble, there is a high linear correlation between the modelled annual-mean temperature increase and shifts in the thermal seasons. Thermal summers lengthen by about 10 days and winters shorten by 10-24 days per 1 degrees C of local warming. In the mid-21st century, about two-thirds of all summers (winters) are projected to be very long (very short) according to the baseline-period standards, with an anomaly greater than 20 days relative to the late-20th century temporal mean. The proportion of years without a thermal winter increases remarkably in the Baltic countries and southern Scandinavian peninsula. Implications of the changing thermal seasons on nature and human society are discussed in a literature review.
  • Palmroth, M.; Tapio, J.; Soucek, A.; Perrels, A.; Jah, M.; Lönnqvist, M.; Nikulainen, M.; Piaulokaite, V.; Seppälä, T.; Virtanen, J. (2021)
    During the last few years, the amount of space debris has been frequently mentioned as a potential risk to current and future space operations. The purpose of this article was to describe the discussions held at the First Sustainable Space Economy Workshop held in Finland 2019. The workshop gathered together experts with economic, legal, regulatory, technological, and environmental backgrounds, with an aim of discussing the sustainable use of space from all these perspectives. As an outcome of these discussions, we find that two concepts, satellite sustainability footprint and orbital capacity, should be introduced at an international level. The satellite sustainability footprint measures how likely the satellite stays healthy and operating, without causing risks to self or others. The orbit capacity is essentially an integral of the footprint over an orbit, and it determines how many satellites of different footprints could be launched to the same orbit. In addition, in this article, we discuss how to realize such concepts within the current normative framework. The authors suggest both top-down and bottom-up approaches, necessitating negotiations within an intergovernmental framework and with the relevant space actors. The most important finding of the workshop and this article, however, is that different space-related fields and experts having diverse backgrounds should continuously discuss in a constructive and informal manner to realize the sustainable utilization of space in practice. (c) 2021 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (
  • Zhang, Mingyang; Li, Tong; Li, Yong; Hui, Pan (2022)
    Urban anomalies may result in loss of life or property if not handled properly. Automatically alerting anomalies in their early stage or even predicting anomalies before happening is of great value for populations. Recently, data-driven urban anomaly analysis frameworks have been forming, which utilize urban big data and machine learning algorithms to detect and predict urban anomalies automatically. In this survey, we make a comprehensive review of the state-of-the-art research on urban anomaly analytics. We first give an overview of four main types of urban anomalies, traffic anomaly, unexpected crowds, environment anomaly, and individual anomaly. Next, we summarize various types of urban datasets obtained from diverse devices, i.e., trajectory, trip records, CDRs, urban sensors, event records, environment data, social media and surveillance cameras. Subsequently, a comprehensive survey of issues on detecting and predicting techniques for urban anomalies is presented. Finally, research challenges and open problems as discussed.