scholarly journals A climatology of wintertime low-level jets in Nares Strait

2021 ◽  
Vol 40 ◽  
Author(s):  
Svenja H.E. Kohnemann ◽  
Günther Heinemann

Intense, southward low-level winds are common in Nares Strait, between Ellesmere Island and northern Greenland. The steep topography along Nares Strait leads to channelling effects, resulting in an along-strait flow. This research study presents a 30-year climatology of the flow regime from simulations of the COSMO-CLM climate model. The simulations are available for the winter periods (November–April) 1987/88 to 2016/17, and thus, cover a period long enough to give robust long-term characteristics of Nares Strait. The horizontal resolution of 15 km is high enough to represent the complex terrain and the meteorological conditions realistically. The 30-year climatology shows that LLJs associated with gap flows are a climatological feature of Nares Strait. The maximum of the mean 10-m wind speed is around 12 m s-1 and is located at the southern exit of Smith Sound. The wind speed is strongly related to the pressure gradient. Single events reach wind speeds of 40 m s-1 in the daily mean. The LLJs are associated with gap flows within the narrowest parts of the strait under stably stratified conditions, with the main LLJ occurring at 100–250 m height. With increasing mountain Froude number, the LLJ wind speed and height increase. The frequency of strong wind events (>20 m s-1 in the daily mean) for the 10 m wind shows a strong interannual variability with an average of 15 events per winter. Channelled winds have a strong impact on the formation of the North Water polynya.

2018 ◽  
Author(s):  
Christoph Schlager ◽  
Gottfried Kirchengast ◽  
Juergen Fuchsberger ◽  
Alexander Kann ◽  
Heimo Truhetz

Abstract. Empirical high-resolution surface wind fields, automatically generated by a weather diagnostic application, the WegenerNet Wind Product Generator (WPG), were intercompared with wind field analysis data from the Integrated Nowcasting through Comprehensive Analysis (INCA) system and with dynamical climate model wind field data from the non-hydrostatic climate model COSMO-CLM. The INCA analysis fields are available at a horizontal grid spacing of 1 km x 1 km, whereas the COSMO model fields are from simulations at a 3 km x 3 km grid. The WPG, developed by Schlager et al. (2017, 2018), generates diagnostic fields at a high resolution grid of 100 m x 100 m, using observations from two dense meteorological station networks: The WegenerNet Feldbach Region (FBR) and its alpine sister network, the WegenerNet Johnsbachtal (JBT). The high-density WegenerNet FBR is located in southeastern Styria, Austria, a region predominated by a hilly terrain and small differences in altitude. The network consists of more than 150 meteorological stations. The WegenerNet JBT contains eleven meteorological stations at elevations ranging from about 600 m to 2200 m in a mountainous region in northern Styria. The wind fields of these different empirical/dynamical modeling approaches were intercompared for thermally induced and strong wind events, using hourly temporal resolutions as supplied by the WPG, with the focus on evaluating spatial differences and displacements between the different datasets. For this comparison, a novel neighborhood-based spatial wind verification methodology based on fractions skill socres (FSS) is used to estimate the modeling performances. All comparisons show an increasing FSS with increasing neighborhood size. In general, the spatial verification indicates a better statistical agreement for the hilly WegenerNet FBR than for the mountainous WegenerNet JBT. The results for the WegenerNet FBR show a better agreement between INCA and WegenerNet than between COSMO and WegenerNet wind fields, especially for large scales (neighborhoods). In particular, COSMO-CLM clearly underperforms in case of thermally induced wind events. For the JBT region, all spatial comparisons indicate little overlap at small neighborhood sizes and in general large biases of wind vectors occur between the dynamical (COSMO) and analysis (INCA) fields and the diagnostic (WegenerNet) reference dataset. Furthermore, gridpoint-based error measures were calculated for the same evaluation cases. The statistical agreement, estimated for the vector-mean wind speed and wind directions show again a better agreement for the WegenerNet FBR than for the WegenerNet JBT region. In general, the difference between modeled and observed wind directions is smaller for strong wind speed events than for thermally induced ones. A combined examination of all spatial and gridpoint-based error measures shows that COSMO-CLM with its limited horizontal resolution of 3 km x 3 km and hence, a too smoothed orography, is not able to represent small-scale wind patterns. The results for the JBT region indicate that the INCA analysis fields generally overestimate wind speeds in the summit regions. For strong wind speed events the wind speed in the valleys is underestimated by INCA, however. Regarding the WegenerNet diagnostic wind fields, the statistics show decent performance in the FBR and somewhat overestimated wind speeds for strong wind speed events in the Enns valley of the JBT region.


2021 ◽  
Author(s):  
Natalia Pillar da Silva ◽  
Rosmeri Porfírio da Rocha ◽  
Natália Machado Crespo ◽  
Ricardo de Camargo ◽  
Jose Antonio Moreira Lima ◽  
...  

<p>This study aims to evaluate how extreme winds (above the 95th percentile) are represented in a downscaling using the regional model WRF over the CORDEX South American domain in an approximate 25 km (0.22 degrees) horizontal resolution, along with CFSR as input. The main focus of the analysis resides over the coastal Brazilian region, given a large number of offshore structures from oil and gas industries subject to impact by severe events. Model results are compared with a reanalysis product (ERA5),  estimates from satellites product (Cross-Calibrated Multi-Platform Wind Speed), and available buoy data (Brazilian National Buoy Project). Downscaling results from WRF show an underestimation of maximum and extreme wind speeds over the region when compared to all references, along with overestimation in the continental areas. This directly impacts results for extreme value estimation for a larger return period and severity evaluation of extreme wind events in future climate projections. To address this, a correction procedure based on the linear relationship between severe wind from satellite and model results is applied. After linearly corrected, the extreme and maximum wind speed values increase and errors in the representation of severe events are reduced in the downscaling results.</p>


2016 ◽  
Author(s):  
Ethan R. Dale ◽  
Adrian J. McDonald ◽  
Jack H.J. Coggins ◽  
Wolfgang Rack

Abstract. Despite warming trends in global temperatures, sea ice extent in the Southern Hemisphere has shown an increasing trend over recent decades. Wind-driven sea ice export from coastal polynyas is an important source of sea ice production. Areas of major polynyas in the Ross Sea, the region with largest increase in sea ice extent, have been suggested to produce a vast amount of the sea ice in the region. We investigate the impacts of strong wind events on the Ross Sea Polynyas and its sea ice concentration and possible consequences on sea ice production. We utilise Bootstrap sea ice concentration (SIC) measurements derived from satellite based, Special Sensor Microwave Imager (SSM/I) brightness temperatures. We compared these with surface winds and temperatures from automatic weather stations (AWS) of the University of Wisconsin-Madison Antarctic Meteorology Program. Our analysis focusses on the austral winter period defined as 1st April to 1st November in this study. Daily data were used to classified into characteristic regimes based on the percentiles of wind speed. For each regime, a composite of SIC anomaly was formed for the Ross Sea region. We found that persistent weak winds near the edge of the Ross Ice Shelf are generally associated with positive SIC anomalies in the Ross Sea Polynya (RSP). Conversely we found negative SIC anomalies in this area during persistent strong winds. By analysing sea ice motion vectors derived from SSM/I and SSMIS brightness temperatures, we find significant sea ice motion anomalies throughout the Ross Sea during strong wind events. These anomalies persist for several days after the strong wind event. Strong, negative correlations are found between SIC and AWS wind speed within the RSP indicating that strong winds cause significant advection of sea ice in the region. We were able to recreate these correlations using co-located ERA-Interim wind speeds. However when only days of a certain percentile based wind speed classification were used, the cross correlation functions produced by ERA-Interim wind speeds differed significantly from those produced using AWS wind speeds. The rapid decrease in SIC during a strong wind event is followed by a more gradual recovery in SIC. This increase occurs on a more gradual time scale than the average persistence of a strong wind event and the resulting sea ice motion anomalies, highlighting the production of new sea ice through thermodynamic processes. In the vicinity of Ross Island, ERA-Interim underestimates wind speeds by a factor of 1.7, which results in a significant misrepresentation of the impact of winds on polynya processes.


2017 ◽  
Vol 30 (14) ◽  
pp. 5455-5471 ◽  
Author(s):  
Neil C. G. Hart ◽  
Suzanne L. Gray ◽  
Peter A. Clark

Extratropical cyclones with damaging winds can have large socioeconomic impacts when they make landfall. During the last decade, studies have identified a mesoscale transient jet, the sting jet, that descends from the tip of the hooked cloud head toward the top of the boundary layer in the dry intrusion region as a cause of strong surface winds, and especially gusts, in some cyclones. While many case studies have focused on the dynamics and characteristics of these jets, there have been few studies that assess the climatology of the associated cyclones and their importance for wind risk. Here the climatological characteristics of North Atlantic cyclones are determined in terms of the possibility that they had sting jets using a previously published sting-jet precursor diagnostic applied to ERA-Interim data over 32 extended winter seasons from 1979 to 2012. Of the 5447 cyclones tracked, 32% had the precursor (42% in the 22% of cyclones that developed explosively). Precursor storms have a more southerly and zonal storm track than storms without the precursor, and precursor storms tend to be more intense as defined by 850-hPa relative vorticity. This study also shows that precursor storms are the dominant cause of cyclone-related resolved strong wind events over the British Isles for 850-hPa wind speeds exceeding 30 m s−1. Hence, early detection of a sting-jet storm could give advance warning of enhanced wind risk. However, over continental northwestern Europe, precursor cyclone-related windstorm events occur far less often.


2020 ◽  
Vol 33 (10) ◽  
pp. 3989-4008 ◽  
Author(s):  
Zhengtai Zhang ◽  
Kaicun Wang

AbstractSurface wind speed (SWS) from meteorological observation, global atmospheric reanalysis, and geostrophic wind speed (GWS) calculated from surface pressure were used to study the stilling and recovery of SWS over China from 1960 to 2017. China experienced anemometer changes and automatic observation transitions in approximately 1969 and 2004, resulting in SWS inhomogeneity. Therefore, we divided the entire period into three sections to study the SWS trend, and found a near-zero annual trend in the SWS in China from 1960 to 1969, a significant decrease of −0.24 m s−1 decade−1 from 1970 to 2004, and a weak recovery from 2005 to 2017. By defining the 95th and 5th percentiles of daily mean wind speeds as strong and weak winds, respectively, we found that the SWS decrease was primarily caused by a strong wind decrease of −8% decade−1 from 1960 to 2017, but weak wind showed an insignificant decreasing trend of −2% decade−1. GWS decreased with a significant trend of −3% decade−1 before the 1990s; during the 1990s, GWS increased with a trend of 3% decade−1 whereas SWS continued to decrease with a trend of 10% decade−1. Consistent with SWS, GWS demonstrated a weak increase after the 2000s. After detrending, both SWS and GWS showed synchronous decadal variability, which is related to the intensity of Aleutian low pressure over the North Pacific. However, current reanalyses cannot reproduce the decadal variability and cannot capture the decreasing trend of SWS either.


2020 ◽  
Author(s):  
Zhengtai Zhang ◽  
Kaicun Wang

<p>Surface wind speed (SWS) from meteorological observation, global atmospheric reanalysis, and geostrophic wind speed (GWS) calculated from surface pressure were used to study the stilling and recovery of SWS over China from 1960 to 2017. China experienced anemometer changes and automatic observation transitions in approximately 1969 and 2004, resulting in SWS inhomogeneity. Therefore, we divided the entire period into three sections to study the SWS trend, and found a near zero annual trend in the SWS in China from 1960 to 1969, a significant decrease of -0.24 m/s decade<sup>-1 </sup>from 1970 to 2004, and a weak recovery from 2005 to 2017. By defining the 95<sup>th</sup> and 5<sup>th</sup> percentiles of monthly mean wind speeds as strong and weak winds, respectively, we found that the SWS decrease was primarily caused by a strong wind decrease of -8 % decade<sup>-1</sup> from 1960 to 2017, but weak wind showed an insignificant decreasing trend of -2 % decade<sup>-1</sup>. GWS decreased with a significant trend of -3 % decade<sup>-1 </sup>before the 1990s, during the 1990s, GWS increased with a trend of 3 % decade<sup>-1 </sup>whereas SWS continued to decrease with a trend of 10 % decade<sup>-1</sup>. Consistent with SWS, GWS demonstrated a weak increase after the 2000s. After detrended, both of SWS and GWS showed synchronous decadal variability, which is related to the intensity of Aleutian low pressure over the North Pacific. However, current reanalyses cannot reproduce the decadal variability, and can not capture the decreasing trend of SWS either.</p>


2019 ◽  
Vol 12 (7) ◽  
pp. 2855-2873
Author(s):  
Christoph Schlager ◽  
Gottfried Kirchengast ◽  
Juergen Fuchsberger ◽  
Alexander Kann ◽  
Heimo Truhetz

Abstract. Empirical high-resolution surface wind fields, automatically generated by a weather diagnostic application, the WegenerNet Wind Product Generator (WPG), were intercompared with wind field analysis data from the Integrated Nowcasting through Comprehensive Analysis (INCA) system and with regional climate model wind field data from the Consortium for Small Scale Modeling Model in Climate Mode (CCLM). The INCA analysis fields are available at a horizontal grid spacing of 1 km × 1 km, whereas the CCLM fields are from simulations at a 3 km × 3 km grid. The WPG, developed by Schlager et al. (2017, 2018), generates diagnostic fields on a high-resolution grid of 100 m × 100 m, using observations from two dense meteorological station networks: the WegenerNet Feldbach Region (FBR), located in a region predominated by a hilly terrain, and its Alpine sister network, the WegenerNet Johnsbachtal (JBT), located in a mountainous region. The wind fields of these different empirical–dynamical modeling approaches were intercompared for thermally induced and strong wind events, using hourly temporal resolutions as supplied by the WPG, with the focus on evaluating spatial differences and displacements between the different datasets. For this comparison, a novel neighborhood-based spatial wind verification methodology based on fractions skill scores (FSSs) is used to estimate the modeling performances. All comparisons show an increasing FSS with increasing neighborhood size. In general, the spatial verification indicates a better statistical agreement for the hilly WegenerNet FBR than for the mountainous WegenerNet JBT. The results for the WegenerNet FBR show a better agreement between INCA and WegenerNet than between CCLM and WegenerNet wind fields, especially for large scales (neighborhoods). In particular, CCLM clearly underperforms in the case of thermally induced wind events. For the JBT region, all spatial comparisons indicate little overlap at small neighborhood sizes, and in general large biases of wind vectors occur between the regional climate model (CCLM) and analysis (INCA) fields and the diagnostic (WegenerNet) reference dataset. Furthermore, grid-point-based error measures were calculated for the same evaluation cases. The statistical agreement, estimated for the vector-mean wind speed and wind directions again show better agreement for the WegenerNet FBR than for the WegenerNet JBT region. A combined examination of all spatial and grid-point-based error measures shows that CCLM with its limited horizontal resolution of 3 km × 3 km, and hence too smoothed an orography, is not able to represent small-scale wind patterns. The results for the JBT region indicate significant biases in the INCA analysis fields, especially for strong wind speed events. Regarding the WegenerNet diagnostic wind fields, the statistics show acceptable performance in the FBR and somewhat overestimated wind speeds for strong wind speed events in the Enns valley of the JBT region.


2021 ◽  
Author(s):  
G. W. K. Moore

Abstract Nares Strait is a major pathway along which multi-year sea ice leaves the Arctic, an ice class that seen a recent dramatic reduction in extent. The winds that blow along the strait play an important role in modulating this ice export as well as in establishing the Arctic’s largest and most productive polynya, the North Water, that forms at its southern terminus. However, its remote location has limited knowledge of the winds along the strait. Here we use automatic weather station from Hans Island, in the middle of the strait, to assess the ability of a set of atmospheric analyses with a common lineage but with varying horizontal resolution to represent the variability in the wind field. We find that the flow is highly bidirectional, consistent with topographic channeling, with the highest wind speeds from the north and that a model resolution of ~9km is required to capture the observed variability. The wind field at Hans Island is also found to be representative of variability in the flow along much of Nares Strait.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
G. W. K. Moore

AbstractNares Strait is a major pathway along which multi-year sea ice leaves the Arctic, an ice class that has seen a recent dramatic reduction in extent. The winds that blow along the strait play an important role in modulating this ice export as well as in establishing the Arctic’s largest and most productive polynya, the North Water, that forms at its southern terminus. However, its remote location has limited our knowledge of the winds along the strait. Here we use automatic weather station data from Hans Island, in the middle of the strait, to assess the ability of a set of atmospheric renalyses and analyses with a common lineage but with varying horizontal resolution to represent the variability in the wind field. We find that the flow is highly bidirectional, consistent with topographic channeling, with the highest wind speeds from the north and that a model resolution of ~ 9 km is required to capture the observed variability. The wind field at Hans Island is also found to be representative of variability in the flow along much of Nares Strait.


2007 ◽  
Vol 46 (4) ◽  
pp. 445-456 ◽  
Author(s):  
Katherine Klink

Abstract Mean monthly wind speed at 70 m above ground level is investigated for 11 sites in Minnesota for the period 1995–2003. Wind speeds at these sites show significant spatial and temporal coherence, with prolonged periods of above- and below-normal values that can persist for as long as 12 months. Monthly variation in wind speed primarily is determined by the north–south pressure gradient, which captures between 22% and 47% of the variability (depending on the site). Regression on wind speed residuals (pressure gradient effects removed) shows that an additional 6%–15% of the variation can be related to the Arctic Oscillation (AO) and Niño-3.4 sea surface temperature (SST) anomalies. Wind speeds showed little correspondence with variation in the Pacific–North American (PNA) circulation index. The effect of the strong El Niño of 1997/98 on the wind speed time series was investigated by recomputing the regression equations with this period excluded. The north–south pressure gradient remains the primary determinant of mean monthly 70-m wind speeds, but with 1997/98 removed the influence of the AO increases at nearly all stations while the importance of the Niño-3.4 SSTs generally decreases. Relationships with the PNA remain small. These results suggest that long-term patterns of low-frequency wind speed (and thus wind power) variability can be estimated using large-scale circulation features as represented by large-scale climatic datasets and by climate-change models.


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