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Interest in Arctic issues has been growing in recent years. From an economic perspective, the Barents Region is of signifi cant interest due to substantial investment projects. The European Union has strengthened its presence and infl uence in the region, playing a role in combatting climate change and optimizing opportunities for northern economic activity. Simultaneously, there have been intentions to narrow the gap between public policy and the private sector to more effi ciently exploit business opportunities in the North. Promoting the Arctic’s potential for business development and building stronger co-operation between the region’s actors are among the recent activities in Arctic development. Innovation hubs generate new businesses from ideas and innovations. They operate in global networks by creating added value and attracting more investment capital and talent. This article explores innovation hubs in three regions in Northern Europe--Oulu (Finland), Luleå (Sweden), and Tromsø (Norway). The article examines, through an innovation hub framework, what kind of business development activities are generating growth in these innovation hubs, and what the diff erences are between these regions. This article discusses whether it is benefi cial to have similar innovation service structures in every region, or if connected Arctic innovation hubs that strengthen Arctic co-operation is a better approach. More intensive co-operation between Arctic actors is most likely to require specifi c actions. [ABSTRACT FROM AUTHOR]

Large shore-parallel, quasi-stationary snow bands are occasionally observed over the Gulf of Finland during wintertime when the sea is not frozen. On the basis of Weather Research and Forecasting mesoscale model experiments and radar observations of snow bands formed in January 2006 and February 2012, we show that their dynamics share common characteristics: (1) the sea gulf that produces the known lake effect, (2) cold easterly large-scale flow along the gulf and (3) a cold local flow from the two near and opposite coastlines of Estonia and Finland in the form of two land-breeze cells which collide offshore. The associated fronts, which have strong rising motions, are maintained by the convergence of the land-breeze cells. In addition to these factors, the concave shape of the coast in the eastern part of the Gulf of Finland promotes offshore convergence and the formation of several secondary bands of precipitation that are adjacent to the eastern part of the main band. When the easterlies turn to southerlies, horizontal convective rolls appear over the sea. The Estonian land breeze is enhanced while the cold air remains stagnant inland over the Finnish coast, acting as an orographic barrier lifting the marine air mass upwards. Consequently, a line of convective precipitation composed of several cells is formed along the Finnish coast. In both events, the simulations also show two low-level jets generated by the combined effects of the land-breeze cells and baroclinicity over the coast of Finland and Estonia. [ABSTRACT FROM AUTHOR]

Large shore-parallel, quasi-stationary snow bands are occasionally observed over the Gulf of Finland during wintertime when the sea is not frozen. On the basis of Weather Research and Forecasting mesoscale model experiments and radar observations of snow bands formed in January 2006 and February 2012, we show that their dynamics share common characteristics: (1) the sea gulf that produces the known lake effect, (2) cold easterly large-scale flow along the gulf and (3) a cold local flow from the two near and opposite coastlines of Estonia and Finland in the form of two land-breeze cells which collide offshore. The associated fronts, which have strong rising motions, are maintained by the convergence of the land-breeze cells. In addition to these factors, the concave shape of the coast in the eastern part of the Gulf of Finland promotes offshore convergence and the formation of several secondary bands of precipitation that are adjacent to the eastern part of the main band. When the easterlies turn to southerlies, horizontal convective rolls appear over the sea. The Estonian land breeze is enhanced while the cold air remains stagnant inland over the Finnish coast, acting as an orographic barrier lifting the marine air mass upwards. Consequently, a line of convective precipitation composed of several cells is formed along the Finnish coast. In both events, the simulations also show two low-level jets generated by the combined effects of the land-breeze cells and baroclinicity over the coast of Finland and Estonia. [ABSTRACT FROM AUTHOR]

We present tropospheric water vapor profiles measured with a Raman lidar during three field campaigns held in Finland. Co-located radio soundings are available throughout the period for the calibration of the lidar signals. We investigate the possibility of calibrating the lidar water vapor profiles in the absence of co-existing on-site soundings using water vapor profiles from the combined Advanced InfraRed Sounder (AIRS) and the Advanced Microwave Sounding Unit (AMSU) satellite product; the Aire Limitée Adaptation dynamique Développement INternational and High Resolution Limited Area Model (ALADIN/HIRLAM) numerical weather prediction (NWP) system, and the nearest radio sounding station located 100 km away from the lidar site (only for the permanent location of the lidar). The uncertainties of the calibration factor derived from the soundings, the satellite and the model data are< 2:8, 7.4 and 3.9%, respectively. We also include water vapor mixing ratio intercomparisons between the radio soundings and the various instruments/model for the period of the campaigns. A good agreement is observed for all comparisons with relative errors that do not exceed 50% up to 8 km altitude in most cases. A 4- year seasonal analysis of vertical water vapor is also presented for the Kuopio site in Finland. During winter months, the air in Kuopio is dry (1:15±0:40 gkg-1); during summer it is wet (5:54±1:02 gkg-1); and at other times, the air is in an intermediate state. These are averaged values over the lowest 2 km in the atmosphere. Above that height a quick decrease in water vapor mixing ratios is observed, except during summer months where favorable atmospheric conditions enable higher mixing ratio values at higher altitudes. Lastly, the seasonal change in disagreement between the lidar and the model has been studied. The analysis showed that, on average, the model underestimates water vapor mixing ratios at high altitudes during spring and summer. [ABSTRACT FROM AUTHOR]

We present tropospheric water vapor profiles measured with a Raman lidar during three field campaigns held in Finland. Co-located radio soundings are available throughout the period for the calibration of the lidar signals. We investigate the possibility of calibrating the lidar water vapor profiles in the absence of co-existing on-site soundings using water vapor profiles from the combined Advanced Infrared Sounder (AIRS) and the Advanced Microwave Radiometer (AMSU) satellite product; the Aire Limitee Adaptation dynamique Development International and High Resolution Limited Area Model (ALADIN-HIRLAM) numerical weather prediction (NWP) system, and the nearest radio sounding station located 100 km away from the lidar site (only for the permanent location of the lidar). The uncertainties of the calibration factor derived from the soundings, the satellite and the model data are < 2.8%, 7.4% and 3.9%, respectively. We also include water vapor mixing ratio intercomparisons between the radio soundings and the various instruments/model for the period of the campaigns. A good agreement is observed for all comparisons with relative errors that do not exceed 50% up to 8 km altitude in most cases. A four-year seasonal analysis of vertical water vapor is also presented for the Kuopio site in Finland. During winter months, the air in Kuopio is dry (1.15 ± 0.40 g kg-1); during summer it is wet (5.54 ± 1.02 g kg-1); and at other times, the air is in an intermediate state. These are averaged values over the lowest 2 km in the atmosphere. Above that height a quick decrease of water vapor mixing ratios is observed, except during summer months where favorable atmospheric conditions enable higher mixing ratio values at higher altitudes. Lastly, the seasonal change in disagreement between the lidar and the model has been studied. The analysis showed that, on average, the model underestimates water vapor mixing ratios at high altitudes during spring and summer. [ABSTRACT FROM AUTHOR]

Two different versions of the operational setup of HIRLAM (High-Resolution Limited-Area Model) at the Finnish Meteorological Institute are exploited in order to verify wind forecasts in the eastern coast of the Gulf of Bothnia. Two cases of interest are studied in detail by also making use of the National Center for Atmospheric Research (NCAR)-Pennsylvania State University mesoscale model (MM5) and a nonhydrostatic version of HIRLAM. Simulations are carried out in both models applied at three horizontal resolutions. The model' sea-land distributions play an essential role in the interpretation of the accuracy of wind speed forecasting. Considering wind direction, all experiments display similar systematic discrepancies. [ABSTRACT FROM AUTHOR]

Atmospheric icing can cause severe damage and danger for many different sectors of society, and accurate forecasts of icing can help mitigate this. The aim of the study is to demonstrate how new ceilometer-based icing observations can be used in icing model verification. The study focuses on icing in the lowest 2 km of the atmosphere. The lowest 400 m of the atmosphere is essential for wind energy production and electricity power lines, while the higher elevations are essential from the aviation point of view. For aviation, the most risky situations are take-offs and landings. The ceilometer observations provide a new way to investigate atmospheric icing. Ceilometers provide vertical profiles of clouds which can be further processed in order to identify in-cloud icing conditions. The new type of ceilometer-based icing observations enables more detailed verification of icing forecasts both in the vertical and in terms of geographical location. Overall, the model shows good skill in predicting clear-sky situations. The verification results show that the icing model performs better for inland areas than for coastal areas, which is attributed to the tendency of the model to forecast clouds, and in-cloud icing, at higher altitudes than observed. [ABSTRACT FROM AUTHOR]

Modern society is very dependent on electricity. In the energy sector, the amount of renewable energy is growing, especially wind energy. To keep the electricity network in balance we need to know how much, when, and where electricity is produced. To support this goal, the need for proper wind forecasts has grown. Compared to traditional deterministic forecasts, ensemble models can better provide the range of variability and uncertainty. However, probabilistic forecasts are often either under- or overdispersive and biased, thus not covering the true and full distribution of probabilities. Hence, statistical postprocessing is needed to increase the value of forecasts. However, traditional closer-to-surface wind observations do not support the verification of wind higher above the surface that is more relevant for wind energy production. Thus, the goal of this study was to test whether new types of observations like radar and lidar winds could be used for verification and statistical calibration of 100-m winds. According to our results, the calibration improved the forecast skill compared to a raw ensemble. The results are better for low and moderate winds, but for higher wind speeds more training data would be needed, either from a larger number of stations or using a longer training period. [ABSTRACT FROM AUTHOR]

OASIS is a multidisciplinary project aiming at a comprehensive quantification of the role of atmospheric aerosols in efficient precipitation enhancement efforts in the United Arab Emirates (UAE). The projects specific scientific objectives are to: 1) undertake a comprehensive 1-year field campaign (Feb 2018 – Feb 2019) in the UAE employing a multitude of in-situ and lidar instruments to quantify the characteristics and the vertical profile of current background aerosol population as well as the key meteorological drivers of cloud formation in the study region, 2) identify optimal seeding strategies (in terms of e.g., time, location, amount of seeding) by using mesoscale meteorological simulations together with cloud-resolving model simulations with a highly advanced aerosol microphysics description, 3) quantify the characteristics of theoretically optimal ice nucleation seed aerosol by employing a suite of molecular-level simulation methods in order to support future experimental work aiming to develop more efficient ice nuclei, and 4) utilize novel statistical approaches to identify the major sources of uncertainty in prediction of rain enhancement success.This presentation summarizes the main results from the first two project years after the completion of the field campaign and a substantial fraction of the mesoscale, cloud-scale and molecular scale modelling work. Our findings highlight the close connection between the aerosol concentrations and the boundary layer dynamics in the UAE atmosphere, illuminate the optimal seeding strategies in both winter stratocumulus and summer convective cloud cases, and point to surface defects as potential sites for efficient ice nucleation. [ABSTRACT FROM AUTHOR]

The aim of this article is to describe the reference configuration of the convection-permitting numerical weather prediction (NWP) model HARMONIE-AROME, which is used for operational short-range weather forecasts in Denmark, Estonia, Finland, Iceland, Ireland, Lithuania, the Netherlands, Norway, Spain, and Sweden. It is developed, maintained, and validated as part of the shared ALADIN-HIRLAM system by a collaboration of 26 countries in Europe and northern Africa on short-range mesoscale NWP. HARMONIE-AROME is based on the model AROME developed within the ALADIN consortium. Along with the joint modeling framework, AROME was implemented and utilized in both northern and southern European conditions by the above listed countries, and this activity has led to extensive updates to the model's physical parameterizations. In this paper the authors present the differences in model dynamics and physical parameterizations compared with AROME, as well as important configuration choices of the reference, such as lateral boundary conditions, model levels, horizontal resolution, model time step, as well as topography, physiography, and aerosol databases used. Separate documentation will be provided for the atmospheric and surface data-assimilation algorithms and observation types used, as well as a separate description of the ensemble prediction system based on HARMONIE-AROME, which is called HarmonEPS. [ABSTRACT FROM AUTHOR]

ABSTRACT Considerable savings in winter road maintenance and accident costs can be achieved with accurate road weather forecasts. Forecasting road surface freezing time accurately enables the timely start of salting and thus ensures safety on roads. The optimal use of road weather observations is essential for the accuracy of short-range road condition forecasts. Road weather models incorporate radiation and other atmospheric variables from numerical weather prediction models. In this study, observations were used to correct the forecast radiation and thus improve road weather forecasts for a set of specific sites. Eighteen different configurations of this methodology were tested for 20 road weather stations in Finland during the autumn-winter period 3 October 2013 to 13 January 2014. This study shows that the coupling method has potential to significantly improve road surface temperature forecasts. Two model configurations in particular turned out to be better than the others giving almost equally good road surface temperature forecasts. It was found that the length of the adjustment period using the corrected radiation had only a slight effect on the results. The outcome of this study can be used to improve road weather models and thus achieve more accurate forecasts. [ABSTRACT FROM AUTHOR]

Highlights: [•] A model was developed for forecasting ragweed pollen emission and transport in air. [•] The model reproduces the main features of ragweed pollen season in Europe. [•] Long-range transport can bring allergy-relevant pollen amounts anywhere in Europe. [ABSTRACT FROM AUTHOR]