StormGeo AS was founded in 1997 and is one of the largest privately held weather service providers worldwide. It provides meteorological services, particularly to the offshore, renewable energy, shipping, corporate enterprise and media industries. It has offices in Norway, United States, Great Britain, UAE, Sweden, Azerbaijan, Brazil, Denmark, Germany and Singapore. The headquarters is located in Bergen, Norway.Through an expansion of its activities and the acquisition of MetConsultancy in 2011 and ImpactWeather in 2012 StormGeo became the number one provider of MetOcean services to the offshore oil and gas industry globally. Wikipedia.
News Article | July 10, 2017
StormGeo's shipping division (formerly AWT) has been collecting data, monitoring data and reporting data on fuel consumption and emissions for over twenty years. More than 60,000 voyages utilized StormGeo's methods of collecting and reporting data in 2016. StormGeo is supporting the new EU regulation and recently has gone the extra step to become EU MRV Certified. According to Michael O'Brien, StormGeo business development manager, "StormGeo is in the unique position to leverage decades of AWT's vessel data collection and reporting to ensure seamless compliance with all facets of the EU MRV regulation. Understanding the importance of MRV compliance, we became certified as an EU MRV provider to give ship owners and managers peace of mind when relying upon our systems." StormGeo's Fleet Performance solution, FleetDSS MRV, incorporates a service level that was created in response to the European Union regulations that ships accurately measure their CO output. FleetDSS MRV provides a tool to help create monitoring plans, view leg-by-leg voyage reports as well as annual emissions reports. In addition, the required reports are sent directly to a verification entity. It includes tools to understand fuel consumption as it relates to performance speed. This gives additional insight into each fleet beyond the MRV regulations. StormGeo's higher level of service, FleetDSS Analytics, provides technical analysis capabilities that enables a user to analyze the performance of a vessel, to compare it to benchmarks as well as to other vessels. The performance can be analyzed with KPIs and graphs and tables to make the best decisions to improve overall performance. This level of FleetDSS has all the key metrics for each vessel to proactively manage fuel efficiency and vessel performance. StormGeo is a global provider of advanced analytics and meteorological services delivering decision support for weather sensitive operations. Since its inception StormGeo has analyzed petabytes of data, transforming it into actionable decision guidance to help customers manage risk and operations, control costs and increase revenue. The company has a leading position in solutions for shipping, offshore oil and gas, renewable energy and onshore business. StormGeo has 23 worldwide offices of which seven are 24/7/365 operation centers. For more information visit www.stormgeo.com. About Verifavia Shipping Verifavia Shipping strives to be the maritime industry's first choice for the provision of efficient, competitive, and flexible emissions verification information and services worldwide. By combining its innovative approach and streamlined procedures with the technical expertise and industry knowledge of its team, Verifavia Shipping provides a top-class service that ensures its customers experience a smooth verification journey. For more information about Verifavia Shipping, please visit http://www.verifavia-shipping.com.
News Article | June 14, 2017
Driven by deep innovation, StormGeo's fleet management solution introduces new analytic tools that can be utilized standalone, or consumed through Application Programming Interfaces (APIs) into customers' existing platforms. These operational solutions include: Additionally, the solutions are fully supported by StormGeo's meteorologists and data scientists through its global network of 24/7 weather centers. "The cost of weather-related delays in the supply chain accounts for billions of dollars. Companies are looking to advanced analytics to predict and improve weather impact, and that's where StormGeo can help. Our holistic supply chain solution spans road, sea and air," Mathew added. Since its inception, StormGeo has analyzed petabytes of data. DeepStorm™, StormGeo's machine learning platform, uncovers complex weather patterns in supply chain logistics that: These predictive analytics can identify latent weather efficiencies, and forecast customers' future freight price exposure, allowing them to buy contracts when the price is favorable. Driven by customers' own Data Lakes, the result delivers new predictive models that challenge how logistics operates today. StormGeo is a global provider of advanced analytics and meteorological services delivering decision support for weather sensitive operations. Since its inception StormGeo has analyzed petabytes of data, transforming it into actionable decision guidance to help customers manage risk and operations, control costs and increase revenue. The company has a leading position in solutions for shipping, offshore oil and gas, renewable energy and onshore business. StormGeo has 23 worldwide offices of which seven are 24/7/365 operation centers. For more information visit www.stormgeo.com. To view the original version on PR Newswire, visit:http://www.prnewswire.com/news-releases/stormgeo-introduces-first-integrated-weather-solution-for-logistics-300473352.html
Kalvig S.,University of Stavanger |
Kalvig S.,StormGeo |
Gudmestad O.T.,University of Stavanger |
Wind Energy | Year: 2014
Onshore wind turbine technology is moving offshore, and the offshore wind industry tends to use larger turbines than those used over land. This calls for an improved understanding of the marine boundary layer. The standards used in the design of offshore wind turbines, particularly the rotor-nacelle assembly, are similar to those used for onshore wind turbines. As a result, simplifications regarding the marine boundary layer are made. Atmospheric stability considerations and wave effects, including the dynamic sea surface roughness, are two major factors affecting flow over sea versus land. Neutral stratification and a flat, smooth sea surface are routinely used as assumptions in wind energy calculations. Newly published literature in the field reveals that the assumption of a neutral stratification is not necessarily a conservative approach. Design tests based on neutral stratification give the lowest fatigue damage on the rotors. Turbulence, heat exchange and momentum transfer depend on the sea state, but this is usually ignored, and the sea surface is thought of as level and smooth. Field experiments and numerical simulations show that during swell conditions, the wind profile will no longer exhibit a logarithmic shape, and the surface drag relies on the sea state. Stratification and sea state are parameters that can be accounted for, and they should therefore be considered in design calculations, energy assessments and power output predictions. Copyright © 2012 John Wiley & Sons, Ltd.
Kalvig S.,University of Stavanger |
Kalvig S.,StormGeo |
Manger E.,Acona Flow Technology |
Hjertager B.,University of Stavanger
Journal of Physics: Conference Series | Year: 2014
The performance of a model wind turbine is simulated with three different CFD methods: actuator disk, actuator line and a fully resolved rotor. The simulations are compared with each other and with measurements from a wind tunnel experiment. The actuator disk is the least accurate and most cost-efficient, and the fully resolved rotor is the most accurate and least cost-efficient. The actuator line method is believed to lie in between the two ends of the scale. The fully resolved rotor produces superior wake velocity results compared to the actuator models. On average it also produces better results for the force predictions, although the actuator line method had a slightly better match for the design tip speed. The open source CFD tool box, OpenFOAM, was used for the actuator disk and actuator line calculations, whereas the market leading commercial CFD code, ANSYS/FLUENT, was used for the fully resolved rotor approach. © Published under licence by IOP Publishing Ltd.
News Article | November 25, 2016
The report "Weather Forecasting Services Market by Industry (Renewable Energy, Oil & Gas, Shipping, Media, Agriculture, Insurance, Retail, Aviation), Purpose (Safety, Operational Efficiency), Forecasting Type (Short, Medium, Long) and Region - Global Forecast to 2021", published by MarketsandMarkets, the weather forecasting services market is projected to grow from USD 1.10 Billion in 2016 to USD 1.56 Billion by 2021, at a CAGR of 7.15% during the forecast period. Browse 75 market data tables and 52 figures spread through 159 pages and in-depth TOC on "Weather Forecasting Services Market - Global Forecast to 2021" http://www.marketsandmarkets.com/Market-Reports/weather-forecasting-services-market-218398014.html Early buyers will receive 10% customization on this report. Factors such rapid industrialization, growth in transportation (aviation and shipping), constant measures to reduce emission of greenhouse gases, increase in the production of clean energy (renewable energy), and increase in demand for more reliable and accurate weather forecast are some of the key factors that are expected to drive the weather forecasting services market during the forecast period. Based on industry, the renewable energy segment is expected to lead the weather forecasting services market during the forecast period On the basis of industry, the Weather Forecasting Services Market has been segmented into renewable energy, oil & gas, shipping, media, agriculture, insurance, retail, aviation, utility, and others. The renewable energy segment is expected to lead the weather forecasting services market during the forecast period. Increase in electricity consumptions and energy requirements for domestic use, and all countries around the globe are facing several challenges in meeting the increased energy demand. Governments are deploying renewable energy efficiently to supplement energy requirements of countries, thereby reducing the emission of greenhouse gases and producing clean energy. All these factors have fueled the growth of the renewable energy industry globally. Based on purpose, the operational efficiency segment is expected to grow at the highest CAGR during the forecast period The weather forecasting services market has been segmented on the basis of purpose into operational efficiency, safety, and others. The operational efficiency segment is anticipated to grow at the highest CAGR during the forecast period. It is expected to lead the weather forecasting services market on account of its purpose of efficiency and economic viability. Increasing demand for renewable energy power plants, growth in international trade between countries, and transportation (shipping and aviation) have resulted in increase in demand for operational efficiency. The Asia Pacific weather forecasting services market is expected to grow at the highest CAGR during the forecast period The weather forecasting services market in Asia-Pacific is estimated to account for the largest share in 2016. The weather forecasting services market in Asia-Pacific is anticipated to grow at the highest CAGR during the forecast period. Factors such as growth in air & sea transport, dependency on rainfall for water, constant measures to increase the production of clean energy, improving economic conditions in the Asia-Pacific region, and increasing concerns for safety & security are driving the Asia-Pacific weather forecasting services market. Major players operating in the weather forecasting services market are StormGeo (Norway), BMT Group (U.K.), Fugro (Netherlands), ENAV spa (Europe), The Weather Company (U.S.), Global Weather Company (U.S.), Mateoblue (U.S.), Precision Weather (U.S.), METEO Group (U.K.), and Met Office (U.K.). Contracts, new product launches, expansions, partnership, collaborations, and agreements are the major growth strategies adopted by the players to strengthen their position in the weather forecasting services market. Browse Related Reports Weather Forecasting Systems Market by End User (Agriculture, Energy, & Others), by Equipment (Barometer, Hygrometer, & Others), by Component (Data Loggers, Sensors, & Others), by System Type, by Forecast Type, and by Geography - Global Forecast to 2020 http://www.marketsandmarkets.com/Market-Reports/meteorological-weather-forecasting-systems-market-29645152.html MarketsandMarkets is the largest market research firm worldwide in terms of annually published premium market research reports. Serving 1700 global fortune enterprises with more than 1200 premium studies in a year, M&M is catering to a multitude of clients across 8 different industrial verticals. We specialize in consulting assignments and business research across high growth markets, cutting edge technologies and newer applications. Our 850 fulltime analyst and SMEs at MarketsandMarkets are tracking global high growth markets following the "Growth Engagement Model - GEM". 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Reeve M.A.,University of Bergen |
Reeve M.A.,Bjerknes Center for Climate Research |
Kolstad E.W.,University of Bergen |
Kolstad E.W.,Bjerknes Center for Climate Research |
Quarterly Journal of the Royal Meteorological Society | Year: 2011
We investigated low-level tip jets generated at the southern tip of the island of Spitsbergen, part of the Svalbard archipelago in the Arctic. Low-level tip jets occur in many locations where airflow converges around obstacles, such as islands. They are often poorly resolved in forecasts or re-analyses, so it is important to document their locations and shed light on why they occur. Tip jets are the result of flow stagnation and flow splitting upstream of an obstacle; both of these processes are dependent on the stability of the air column, wind speed and direction upstream. Jets generated around Sørkapp, the southern cape of Spitsbergen, have been resolved previously in numerical studies, but no climatology exists. In this study, we used the Weather Research and Forecasting model (WRF) to demonstrate the influence of topography on the development of tip jets. We used QuikSCAT satellite-derived surface wind data to identify tip jet events and compile climatologies, and the ERA-Interim data to investigate the prevailing synoptic conditions during jet events and identify the main driving forces. We found that tip jets can occur throughout the year, associated with a negative surface-level pressure anomaly moving in a northeast direction from the Norwegian Sea and towards the Barents Sea. On average, jets occurred just over 8% of days throughout the year. The maximum 60-day running mean of occurrence was around 12% and occurred between February and March. The results showed that negative wind speed and positive static stability anomalies were statistically significant upstream of the island group. These anomalies remain significant when seasons of high, middle and low occurrence were analysed separately. We conclude therefore that wind direction persistence may play an important role in the seasonality of jet occurrences in the study region. © 2011 Royal Meteorological Society.
Krogsaeter O.,StormGeo |
Reuder J.,University of Bergen
Wind Energy | Year: 2015
Five different planetary boundary layer (PBL) schemes in the Weather Research and Forecasting (WRF) model have been tested with respect to their capability to model boundary layer parameters relevant for offshore wind deployments. For the year 2005, model simulations based on the YSU, ACM2, QNSE, MYJ and MYNN2 PBL schemes with WRF have been performed for the North Sea and validated against measurements from the FINO1 platform. In part I, the investigations had focused on the key parameters 100 m mean wind speed and wind shear in terms of the power-law exponent. In part II, the focus is now set on the capability of the model to represent height and stability of the marine atmospheric boundary layer.Considerable differences are found among the PBL schemes in predicting the PBL height. A substantial part of this variation is explained by the use of different PBL-height definitions in the schemes. The use of a standardized procedure in calculating the PBL height from common WRF output parameters, in particular the temperature gradient and the wind shear, leads to reduced differences between the different schemes and a closer correspondence with the FINO1 measurements. The study also reveals a very clear seasonal dependency of the atmospheric stability over Southern North Sea. During winter time, the marine atmospheric boundary layer is more or less neutral with several episodes of unstable periods. During spring and early summer, the occurrence of periods with very stable stratification becomes dominant with stable conditions up to 40-45% of the time when warm continental air is advected from the South. In general, the results of part II confirm again that the MYJ scheme performs slightly better than the others and can therefore be suggested as first choice for marine atmospheric boundary layer simulations without a priori information of atmospheric stability in the region of interest. Copyright © 2014 John Wiley & Sons, Ltd.
Kolstad E.W.,StormGeo |
Kolstad E.W.,University of Bergen
Climate Dynamics | Year: 2015
The Barents Sea is mostly ice-free during winter and therefore prone to severe weather associated with marine cold air outbreaks, such as polar lows. With the increasing marine activity in the region, it is important to study the climatology and variability of episodes with strong winds, as well as to understand their causes. Explosive marine cyclogenesis is usually caused by a combination of several mechanisms: upper-level forcing, stratospheric dry intrusions, latent heat release, surface energy fluxes, low-level baroclinicity. An additional factor that has been linked to extremely strong surface winds, is low static stability in the lower atmosphere, which allows for downward transfer of high-momentum air. Here the most extreme small-scale wind episodes in a high-resolution (5 km) 35-year hindcast were analyzed, and it was found that they were associated with unusually strong low-level baroclinicity and surface heat fluxes. And crucially, the 12 most severe episodes had stronger cold-air advection than 12 slightly less severe cases, suggesting that marine cold air outbreaks are the most important mechanism for extreme winds on small spatial scales over the Barents Sea. Because weather models are often unable to explicitly forecast small-scale developments in data-sparse regions such as the Barents Sea, these results can be used by forecasters as supplements to forecast model data. © 2014 Springer-Verlag Berlin Heidelberg
Storen E.N.,University of Bergen |
Storen E.N.,Bjerknes Center for Climate Research |
Kolstad E.W.,Bjerknes Center for Climate Research |
Kolstad E.W.,StormGeo |
And 2 more authors.
Journal of Quaternary Science | Year: 2012
Analysis of two continuous, high-resolution palaeo-flood records from southern Norway reveals that the frequency of extreme flood events has changed significantly during the Holocene. During the early and middle Holocene, flood frequency was low; by contrast, it was high over the last 2300 years when the mean flood frequency was about 2.5-3.0 per century. The present regional discharge regime is dominated by spring/summer snowmelt, and our results indicate that the changing flood frequency cannot be explained by local conditions associated with the respective catchments of the two lakes, but rather long-term variations of solid winter precipitation and related snowmelt. Applying available instrumental winter precipitation data and associated sea-level pressure re-analysis data as a modern analogue, we document that atmospheric circulation anomalies, significantly different from the North Atlantic Oscillation (NAO), have some potential in explaining the variability of the two different palaeo-flood records. Centennial-scale patterns in shifting flood frequency might be indicative of shifts in atmospheric circulation and shed light on palaeo-pressure variations in the North Atlantic region, in areas not influenced by the NAO. Major shifts are found at about 2300, 1200 and 200 years ago (cal. a BP). © 2011 John Wiley & Sons, Ltd.