scholarly journals Changing cyclones and surface wind speeds over the North Atlantic and Europe in a transient GHG experiment

2000 ◽  
Vol 15 ◽  
pp. 109-122 ◽  
Author(s):  
P Knippertz ◽  
U Ulbrich ◽  
P Speth
Keyword(s):  
North Atlantic ◽  
Surface Wind ◽  
Wind Speeds ◽  
The North ◽  
The North Atlantic

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>

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>

scholarly journals Observational Assessment of Nonlocal Heat Flux Feedback in the North Atlantic by GEFA

2013 ◽  
Vol 52 (3) ◽  
pp. 645-653 ◽  
Author(s):  
Na Wen ◽  
Zhengyu Liu ◽  
Qinyu Liu
Keyword(s):  
Heat Flux ◽  
North Atlantic ◽  
Surface Wind ◽  
Turbulent Heat ◽  
Observational Assessment ◽  
The North ◽  
The North Atlantic ◽  
Flux Response ◽  
Sst Anomalies ◽  
Heat Flux Feedback

AbstractMost previous studies have proven the local negative heat flux feedback (the surface heat flux response to SST anomalies) in the midlatitude areas. However, it is uncertain whether a nonlocal heat flux feedback can be observed. In this paper, the generalized equilibrium feedback assessment (GEFA) method is employed to examine the full surface turbulent heat flux response to SST in the North Atlantic Ocean using NCEP–NCAR reanalysis data. The results not only confirm the dominant local negative feedback, but also indicate a robust nonlocal positive feedback of the Gulf Stream Extension (GSE) SST to the downstream heat flux in the subpolar region. This nonlocal feedback presents a strong seasonality, with response magnitudes of in winter and in summer. Further study indicates that the nonlocal effect is initiated by the adjustments of the downstream surface wind to the GSE SST anomalies.

what do we not know about the sea-surface wind stress1

1968 ◽  
Vol 49 (3) ◽  
pp. 247-253 ◽  
Author(s):  
E. B. Kraus
Keyword(s):  
Drag Coefficient ◽  
North Atlantic ◽  
Surface Stress ◽  
Surface Wind ◽  
Sea Surface ◽  
The North ◽  
Sea Surface Wind ◽  
The North Atlantic ◽  
Simple Sampling ◽  
Range Of Values

A simple sampling experiment gives a several octave range of values for the zonal surface stress obtainable from synoptic maps over the North Atlantic. Uncertainty about the value of the drag coefficient account for about half the variance. The different methods that have been used to specify this quantity are reviewed and an attempt is made to state explicitly the assumptions involved in each case.

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 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.

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

<p>Surface winds — both wind speed and vector wind components — 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‐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‐resolution data. It is one of the ways to avoid costly high‐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‐of‐the‐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‐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.</p><p>This work was undertaken with financial support by the Russian Science Foundation grant № 17-77-20112-P.</p>

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