Estimation of Weibull distribution for wind speeds along ship routes

2016 ◽  
Vol 231 (2) ◽  
pp. 464-480 ◽  
Author(s):  
Wengang Mao ◽  
Igor Rychlik
Keyword(s):  
Wind Speed ◽  
Weibull Distribution ◽  
North Atlantic ◽  
Gaussian Model ◽  
Energy Harvest ◽  
Wind Speeds ◽  
The North ◽  
Significant Difference ◽  
The North Atlantic ◽  
Wind Distribution

In order to evaluate potential benefits of new green shipping concepts that utilize wind power as auxiliary propulsion in ships or of offshore wind energy harvest, it is essential to have reliable wind speed statistics. A new method to find parameters in the Weibull distribution is given. It can be used either at a fixed offshore position or along arbitrary ship routes. The method employs a spatio-temporal transformed Gaussian model for wind speed variability. The model was fitted to 10 years’ ERA-Interim reanalysis data of wind speed. The proposed method to derive Weibull distribution is validated using wind speeds measured on-board by vessels sailing in the North Atlantic and the west region of the Mediterranean Sea. For the westbound voyages in the North Atlantic, the proposed method gives a good approximation of the observed wind distribution along those ship routes. For the eastbound voyages, significant difference is found between the observed wind distribution and that approximated by the proposed method. The suspected reason is attributed to the ship routing decisions of masters and software. Hence, models that consider only the wind climate description need to be supplemented with a method to take into account the effect of wind-aware routing plan.

scholarly journals Air/sea DMS gas transfer in the North Atlantic: evidence for limited interfacial gas exchange at high wind speed

2013 ◽  
Vol 13 (5) ◽  
pp. 13285-13322 ◽  
Author(s):  
T. G. Bell ◽  
W. De Bruyn ◽  
S. D. Miller ◽  
B. Ward ◽  
K. Christensen ◽  
...  
Keyword(s):  
Wind Speed ◽  
North Atlantic ◽  
Interfacial Stress ◽  
Horizontal Wind ◽  
Gas Transfer ◽  
High Wind ◽  
High Wind Speed ◽  
Wind Speeds ◽  
The North ◽  
The North Atlantic

Abstract. Shipboard measurements of eddy covariance DMS air/sea fluxes and seawater concentration were carried out in the North Atlantic bloom region in June/July 2011. Gas transfer coefficients (k660) show a linear dependence on mean horizontal wind speed at wind speeds up to 11 m s−1. At higher wind speeds the relationship between k660 and wind speed weakens. At high winds, measured DMS fluxes were lower than predicted based on the linear relationship between wind speed and interfacial stress extrapolated from low to intermediate wind speeds. In contrast, the transfer coefficient for sensible heat did not exhibit this effect. The apparent suppression of air/sea gas flux at higher wind speeds appears to be related to sea state, as determined from shipboard wave measurements. These observations are consistent with the idea that long waves suppress near surface water side turbulence, and decrease interfacial gas transfer. This effect may be more easily observed for DMS than for less soluble gases, such as CO2, because the air/sea exchange of DMS is controlled by interfacial rather than bubble-mediated gas transfer under high wind speed conditions.

scholarly journals Air–sea dimethylsulfide (DMS) gas transfer in the North Atlantic: evidence for limited interfacial gas exchange at high wind speed

2013 ◽  
Vol 13 (21) ◽  
pp. 11073-11087 ◽  
Author(s):  
T. G. Bell ◽  
W. De Bruyn ◽  
S. D. Miller ◽  
B. Ward ◽  
K. H. Christensen ◽  
...  
Keyword(s):  
Wind Speed ◽  
North Atlantic ◽  
Interfacial Stress ◽  
Horizontal Wind ◽  
Gas Transfer ◽  
High Wind ◽  
High Wind Speed ◽  
Wind Speeds ◽  
The North ◽  
The North Atlantic

Abstract. Shipboard measurements of eddy covariance dimethylsulfide (DMS) air–sea fluxes and seawater concentration were carried out in the North Atlantic bloom region in June/July 2011. Gas transfer coefficients (k660) show a linear dependence on mean horizontal wind speed at wind speeds up to 11 m s−1. At higher wind speeds the relationship between k660 and wind speed weakens. At high winds, measured DMS fluxes were lower than predicted based on the linear relationship between wind speed and interfacial stress extrapolated from low to intermediate wind speeds. In contrast, the transfer coefficient for sensible heat did not exhibit this effect. The apparent suppression of air–sea gas flux at higher wind speeds appears to be related to sea state, as determined from shipboard wave measurements. These observations are consistent with the idea that long waves suppress near-surface water-side turbulence, and decrease interfacial gas transfer. This effect may be more easily observed for DMS than for less soluble gases, such as CO2, because the air–sea exchange of DMS is controlled by interfacial rather than bubble-mediated gas transfer under high wind speed conditions.

Navigation and Traffic Control over the North Atlantic

1957 ◽  
Vol 10 (2) ◽  
pp. 115-132
Author(s):  
D. O. Fraser
Keyword(s):  
North Atlantic ◽  
Traffic Control ◽  
Traffic Density ◽  
Aircraft Accidents ◽  
The North ◽  
Natural Tendency ◽  
Significant Difference ◽  
The North Atlantic ◽  
Wind Distribution ◽  
High Traffic Density

At present the total number of military and civil flights across the North Atlantic is about 130 per day counting both directions. Once aircraft are outside the systems of airways used in the high traffic density areas over each continent there are no fixed traffic lanes and aircraft plan their flights independently, generally following composite tracks to take maximum advantage of the wind distribution. Pilots are familiar with the natural tendency for tracks to diverge even when aircraft are being navigated via the same route but when the navigator in each aircraft is following an independent flight plan the separation of tracks will be much greater. Thus on the 2000-mile North Atlantic route the traffic density in real terms—say the number of aircraft per 10,000 square miles—is extremely low, and it is open to question whether the chance of two aircraft colliding in mid-Atlantic is not so remote as to be treated as an impossibility for practical purposes. This may sound heretical but if, as the writer suspects, the chance is so low as to make no significant difference to the overall risk of aircraft accidents, then there are other aspects of aircraft operation where the attention now being given to Atlantic traffic control might yield quicker dividends in the improvement of air safety.

Seasonal Predictability of Wintertime mid-latitude Cyclonic Activity over the North Atlantic and Europe

2021 ◽  
Author(s):  
Alvise Aranyossy ◽  
Sebastian Brune ◽  
Lara Hellmich ◽  
Johanna Baehr
Keyword(s):  
North Atlantic ◽  
Large Scale ◽  
Jet Stream ◽  
Cyclonic Activity ◽  
Max Planck ◽  
Pressure System ◽  
Wind Speeds ◽  
Average Lifespan ◽  
The North ◽  
The North Atlantic

<p>We analyse the connections between the wintertime North Atlantic Oscillation (NAO), the eddy-driven jet stream with the mid-latitude cyclonic activity over the North Atlantic and Europe. We investigate, through the comparison against ECMWF ERA5 and hindcast simulations from the Max Planck Institute Earth System Model (MPI-ESM), the potential for enhancement of the seasonal prediction skill of the Eddy Kinetic Energy (EKE) by accounting for the connections between large-scale climate and the regional cyclonic activity. Our analysis focuses on the wintertime months (December-March) in the 1979-2019 period, with seasonal predictions initialized every November 1st. We calculate EKE from wind speeds at 250 hPa, which we use as a proxy for cyclonic activity. The zonal and meridional wind speeds are bandpass filtered with a cut-off at 3-10 days to fit with the average lifespan of mid-latitude cyclones. </p><p>Preliminary results suggest that in ERA5, major positive anomalies in EKE, both in quantity and duration, are correlated with a northern position of the jet stream and a positive phase of the NAO. Apparently, a deepened Icelandic low-pressure system offers favourable conditions for mid-latitude cyclones in terms of growth and average lifespan. In contrast, negative anomalies in EKE over the North Atlantic and Central Europe are associated with a more equatorward jet stream, these are also linked to a negative phase of the NAO.  Thus, in ERA5, the eddy-driven jet stream and the NAO play a significant role in the spatial and temporal distribution of wintertime mid-latitude cyclonic activity over the North Atlantic and Europe. We extend this connection to the MPI-ESM hindcast simulations and present an analysis of their predictive skill of EKE for wintertime months.</p>

Near-surface wind speeds in ERA5: Climatology, decadal variability and long-term trends

2021 ◽  
Author(s):  
Terhi K. Laurila ◽  
Victoria A. Sinclair ◽  
Hilppa Gregow
Keyword(s):  
Iberian Peninsula ◽  
North Atlantic ◽  
Decadal Variability ◽  
Surface Wind ◽  
Northern Europe ◽  
Near Surface ◽  
Wind Speeds ◽  
The North ◽  
The North Atlantic

<p>The knowledge of long-term climate and variability of near-surface wind speeds is essential and widely used among meteorologists, climate scientists and in industries such as wind energy and forestry. The new high-resolution ERA5 reanalysis from the European Centre for Medium-Range Weather Forecasts (ECMWF) will likely be used as a reference in future climate projections and in many wind-related applications. Hence, it is important to know what is the mean climate and variability of wind speeds in ERA5.</p><p>We present the monthly 10-m wind speed climate and decadal variability in the North Atlantic and Europe during the 40-year period (1979-2018) based on ERA5. In addition, we examine temporal time series and possible trends in three locations: the central North Atlantic, Finland and Iberian Peninsula. Moreover, we investigate what are the physical reasons for the decadal changes in 10-m wind speeds.</p><p>The 40-year mean and the 98th percentile wind speeds show a distinct contrast between land and sea with the strongest winds over the ocean and a seasonal variation with the strongest winds during winter time. The winds have the highest values and variabilities associated with storm tracks and local wind phenomena such as the mistral. To investigate the extremeness of the winds, we defined an extreme find factor (EWF) which is the ratio between the 98th percentile and mean wind speeds. The EWF is higher in southern Europe than in northern Europe during all months. Mostly no statistically significant linear trends of 10-m wind speeds were found in the 40-year period in the three locations and the annual and decadal variability was large.</p><p>The windiest decade in northern Europe was the 1990s and in southern Europe the 1980s and 2010s. The decadal changes in 10-m wind speeds were largely explained by the position of the jet stream and storm tracks and the strength of the north-south pressure gradient over the North Atlantic. In addition, we investigated the correlation between the North Atlantic Oscillation (NAO) and the Atlantic Multi-decadal Oscillation (AMO) in the three locations. The NAO has a positive correlation in the central North Atlantic and Finland and a negative correlation in Iberian Peninsula. The AMO correlates moderately with the winds in the central North Atlantic but no correlation was found in Finland or the Iberian Peninsula. Overall, our study highlights that rather than just using long-term linear trends in wind speeds it is more informative to consider inter-annual or decadal variability.</p>

scholarly journals The Global Wind Resource Observed by Scatterometer

2020 ◽  
Vol 12 (18) ◽  
pp. 2920 ◽  
Author(s):  
Ian R. Young ◽  
Ebru Kirezci ◽  
Agustinus Ribal
Keyword(s):  
North Atlantic ◽  
Extreme Value Analysis ◽  
Data Set ◽  
Value Analysis ◽  
Wind Speeds ◽  
The North ◽  
Extreme Wind ◽  
Basin Scale ◽  
The North Atlantic ◽  
Wind Resource

A 27-year-long calibrated multi-mission scatterometer data set is used to determine the global basin-scale and near-coastal wind resource. In addition to mean and percentile values, the analysis also determines the global values of both 50- and 100-year return period wind speeds. The analysis clearly shows the seasonal variability of wind speeds and the differing response of the two hemispheres. The maximum wind speeds in each hemisphere are comparable but there is a much larger seasonal cycle in the northern hemisphere. As a result, the southern hemisphere has a more consistent year-round wind climate. Hence, coastal regions of southern Africa, southern Australia, New Zealand and southern South America appear particularly suited to coastal and offshore wind energy projects. The extreme value analysis shows that the highest extreme wind speeds occur in the North Atlantic Ocean with extreme wind regions concentrated along the western boundaries of the North Atlantic and North Pacific Oceans and the Indian Ocean sector of the Southern Ocean. The signature of tropical cyclones is clearly observed in each of the well-known tropical cyclone basins.

scholarly journals Factors driving the seasonal and hourly variability of sea-spray aerosol number in the North Atlantic

2019 ◽  
Vol 116 (41) ◽  
pp. 20309-20314 ◽  
Author(s):  
Georges Saliba ◽  
Chia-Li Chen ◽  
Savannah Lewis ◽  
Lynn M. Russell ◽  
Laura-Helena Rivellini ◽  
...  
Keyword(s):  
Wind Speed ◽  
North Atlantic ◽  
Climate Models ◽  
Marine Boundary Layer ◽  
Phytoplankton Bloom ◽  
Cloud Condensation Nuclei ◽  
Sea Spray ◽  
Wind Speeds ◽  
The North ◽  
Sea Spray Aerosol

Four North Atlantic Aerosol and Marine Ecosystems Study (NAAMES) field campaigns from winter 2015 through spring 2018 sampled an extensive set of oceanographic and atmospheric parameters during the annual phytoplankton bloom cycle. This unique dataset provides four seasons of open-ocean observations of wind speed, sea surface temperature (SST), seawater particle attenuation at 660 nm (cp,660, a measure of ocean particulate organic carbon), bacterial production rates, and sea-spray aerosol size distributions and number concentrations (NSSA). The NAAMES measurements show moderate to strong correlations (0.56 < R < 0.70) between NSSA and local wind speeds in the marine boundary layer on hourly timescales, but this relationship weakens in the campaign averages that represent each season, in part because of the reduction in range of wind speed by multiday averaging. NSSA correlates weakly with seawater cp,660 (R = 0.36, P << 0.01), but the correlation with cp,660, is improved (R = 0.51, P < 0.05) for periods of low wind speeds. In addition, NAAMES measurements provide observational dependence of SSA mode diameter (dm) on SST, with dm increasing to larger sizes at higher SST (R = 0.60, P << 0.01) on hourly timescales. These results imply that climate models using bimodal SSA parameterizations to wind speed rather than a single SSA mode that varies with SST may overestimate SSA number concentrations (hence cloud condensation nuclei) by a factor of 4 to 7 and may underestimate SSA scattering (hence direct radiative effects) by a factor of 2 to 5, in addition to overpredicting variability in SSA scattering from wind speed by a factor of 5.

Comparison of AI-based approaches for statistical downscaling of surface wind fields in the North Atlantic

2021 ◽  
Author(s):  
Vadim Rezvov ◽  
Mikhail Krinitskiy ◽  
Alexander Gavrikov ◽  
Sergey Gulev
Keyword(s):  
Wind Speed ◽  
Statistical Downscaling ◽  
North Atlantic ◽  
Surface Wind ◽  
Surface Winds ◽  
Wind Fields ◽  
The North ◽  
The North Atlantic ◽  
Vector Wind ◽  
Resolution Data

&lt;p&gt;Surface winds &amp;#8212; both wind speed and vector wind components &amp;#8212; are fields of fundamental climatic importance. The character of surface winds greatly influences (and is influenced by) surface exchanges of momentum, energy, and matter. These wind fields are of interest in their own right, particularly concerning the characterization of wind power density and wind extremes. Surface winds are influenced by small-scale features such as local topography and thermal contrasts. That is why accurate high-resolution prediction of near&amp;#8208;surface wind fields is a topic of central interest in various fields of science and industry. Statistical downscaling is the way for inferring information on physical quantities at a local scale from available low&amp;#8208;resolution data. It is one of the ways to avoid costly high&amp;#8208;resolution simulations. Statistical downscaling connects variability of various scales using statistical prediction models. This approach is fundamentally data-driven and can only be applied in locations where observations have been taken for a sufficiently long time to establish the statistical relationship. Our study considered statistical downscaling of surface winds (both wind speed and vector wind components) in the North Atlantic. Deep learning methods are among the most outstanding examples of state&amp;#8208;of&amp;#8208;the&amp;#8208;art machine learning techniques that allow approximating sophisticated nonlinear functions. In our study, we applied various approaches involving artificial neural networks for statistical downscaling of near&amp;#8208;surface wind vector fields. We used ERA-Interim reanalysis as low-resolution data and RAS-NAAD dynamical downscaling product (14km grid resolution) as a high-resolution target. We compared statistical downscaling results to those obtained with bilinear/bicubic interpolation with respect to downscaling quality. We investigated how network complexity affects downscaling performance. We will demonstrate the preliminary results of the comparison and propose the outlook for further development of our methods.&lt;/p&gt;&lt;p&gt;This work was undertaken with financial support by the Russian Science Foundation grant &amp;#8470; 17-77-20112-P.&lt;/p&gt;

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