scholarly journals Catch Characteristics of Precipitation Gauges in High-Latitude Regions with High Winds

2006 ◽  
Vol 7 (5) ◽  
pp. 984-994 ◽  
Author(s):  
Konosuke Sugiura ◽  
Tetsuo Ohata ◽  
Daqing Yang
Keyword(s):  
Wind Speed ◽  
High Latitude ◽  
Cold Climate ◽  
Strong Wind ◽  
Blowing Snow ◽  
High Wind ◽  
Wind Speeds ◽  
Solid Precipitation ◽  
High Winds ◽  
Correction Equations

Abstract Intercomparison of solid precipitation measurement at Barrow, Alaska, has been carried out to examine the catch characteristics of various precipitation gauges in high-latitude regions with high winds and to evaluate the applicability of the WMO precipitation correction procedures. Five manual precipitation gauges (Canadian Nipher, Hellmann, Russian Tretyakov, U.S. 8-in., and Wyoming gauges) and a double fence intercomparison reference (DFIR) as an international reference standard have been installed. The data collected in the last three winters indicates that the amount of solid precipitation is characteristically low, and the zero-catch frequency of the nonshielded gauges is considerably high, 60%–80% of precipitation occurrences. The zero catch in high-latitude high-wind regions becomes a significant fraction of the total precipitation. At low wind speeds, the catch characteristics of the gauges are roughly similar to the DFIR, although it is noteworthy that the daily catch ratios decreased more rapidly with increasing wind speed compared to the WMO correction equations. The dependency of the daily catch ratios on air temperature was confirmed, and the rapid decrease in the daily catch ratios is due to small snow particles caused by the cold climate. The daily catch ratio of the Wyoming gauge clearly shows wind-induced losses. In addition, the daily catch ratios are considerably scattered under strong wind conditions due to the influence of blowing snow. This result suggests that it is not appropriate to extrapolate the WMO correction equations for the shielded gauges in high-latitude regions for high wind speed of over 6 m s−1.

Investigation of weather conditions and tropospheric BrO transport during Bromine Explosion Events in the Arctic and ozone depletion in Ny-Ålesund observed by satellite and ground-based remote sensing

2021 ◽  
Author(s):  
Bianca Zilker ◽  
Anne-Marlene Blechschmidt ◽  
Sora Seo ◽  
Ilias Bougoudis ◽  
Tim Bösch ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Detection Limit ◽  
Wind Speed ◽  
Ozone Depletion ◽  
Weather Conditions ◽  
Tropospheric Chemistry ◽  
The Arctic ◽  
Blowing Snow ◽  
High Wind ◽  
Wind Speeds

<p align="justify">Bromine Explosion Events (BEEs) have been observed since the late 1990s in the Arctic and Antarctic during polar spring and play an important role in tropospheric chemistry. In a heterogeneous, autocatalytic, chemical chain reaction cycle, inorganic bromine is released from the cryosphere into the troposphere and depletes ozone often to below detection limit. Ozone is a source of the most important tropospheric oxidizing agent OH and the oxidizing capacity and radiative forcing of the troposphere are thus being impacted. Bromine also reacts with gaseous mercury, thereby facilitating the deposition of toxic mercury, which has adverse environmental impacts. C<span lang="en-US">old saline surfaces, such as young sea ice, frost flowers, and snow are likely bromine sources </span><span lang="en-US">during BEEs. </span><span lang="en-US">D</span>ifferent meteorological conditions seem to favor the development of these events: on the one hand, low wind speeds and a stable boundary layer, where bromine can accumulate and deplete ozone, and on the other hand, high wind speeds above approximately 10 m/s with blowing snow and a higher unstable boundary layer. In high wind speed conditions – occurring for example along fronts of polar cyclones – recycling of bromine on snow and aerosol surfaces may take place aloft.</p> <p align="justify">To improve the understanding of weather conditions and bromine sources leading to the development of BEEs, case studies using high resolution S5P TROPOMI retrievals of tropospheric BrO together with meteorological simulations by the WRF model and Lagrangian transport simulations of BrO by FLEXPART-WRF are carried out. WRF simulations show, that high tropospheric BrO columns observed by TROPOMI often coincide with areas of high wind speeds. This probably points to release of bromine from blowing snow with cold temperatures favoring the bromine explosion reactions. However, some BrO plumes are observed over areas with very low wind speed and a stable low boundary layer. To monitor the amount of ozone depleted during a BEE, ozone sonde measurements from Ny-Ålesund are compared with MAX-DOAS BrO profiles. First evaluations show a drastic decrease in ozone, partly below the detection limit, while measuring enhanced BrO values at the same time. <span lang="en-US">In order to analyze </span><span lang="en-US">the possible origin</span><span lang="en-US"> of the BrO </span><span lang="en-US">plume </span><span lang="en-US">arriving in </span><span lang="en-US">Ny-</span><span lang="en-US">Å</span><span lang="en-US">lesund</span><span lang="en-US">, </span><span lang="en-US">and to investigate its transportation route, </span><span lang="en-US">FLEXPART-WRF runs are </span><span lang="en-US">executed </span><span lang="en-US">for the times of observed ozone depletion.</span></p> <p align="justify"> </p> <p align="justify"><em>This work was supported by the</em><em> DFG funded Transregio-project TR 172 “Arctic Amplification </em>(AC)<sup>3</sup><em>“.</em></p>

scholarly journals A social Beaufort scale to detect high winds using language in social media posts

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Iain S. Weaver ◽  
Hywel T. P. Williams ◽  
Rudy Arthur
Keyword(s):  
Social Media ◽  
Wind Speed ◽  
Temporal Correlation ◽  
Weather Conditions ◽  
Local Area ◽  
High Wind ◽  
Wind Speeds ◽  
The Uk ◽  
The Relationship ◽  
High Winds

AbstractPeople often talk about the weather on social media, using different vocabulary to describe different conditions. Here we combine a large collection of wind-related Twitter posts (tweets) and UK Met Office wind speed observations to explore the relationship between tweet volume, tweet language and wind speeds in the UK. We find that wind speeds are experienced subjectively relative to the local baseline, so that the same absolute wind speed is reported as stronger or weaker depending on the typical weather conditions in the local area. Different linguistic tokens (words and emojis) are associated with different wind speeds. These associations can be used to create a simple text classifier to detect ‘high-wind’ tweets with reasonable accuracy; this can be used to detect high winds in a locality using only a single tweet. We also construct a ‘social Beaufort scale’ to infer wind speeds based only on the language used in tweets. Together with the classifier, this demonstrates that language alone is indicative of weather conditions, independent of tweet volume. However, the number of high-wind tweets shows a strong temporal correlation with local wind speeds, increasing the ability of a combined language-plus-volume system to successfully detect high winds. Our findings complement previous work in social sensing of weather hazards that has focused on the relationship between tweet volume and severity. These results show that impacts of wind and storms are found in how people communicate and use language, a novel dimension in understanding the social impacts of extreme weather.

scholarly journals Bayesian Model Averaging for Wind Speed Ensemble Forecasts Using Wind Speed and Direction

2017 ◽  
Vol 32 (6) ◽  
pp. 2217-2227 ◽  
Author(s):  
Siri Sofie Eide ◽  
John Bjørnar Bremnes ◽  
Ingelin Steinsland
Keyword(s):  
Wind Speed ◽  
Wind Direction ◽  
Bayesian Model Averaging ◽  
Weather Prediction ◽  
Model Averaging ◽  
Strong Wind ◽  
Ensemble Forecasts ◽  
Wind Speeds ◽  
Low Wind Speeds ◽  
The One

Abstract In this paper, probabilistic wind speed forecasts are constructed based on ensemble numerical weather prediction (NWP) forecasts for both wind speed and wind direction. Including other NWP variables in addition to the one subject to forecasting is common for statistical calibration of deterministic forecasts. However, this practice is rarely seen for ensemble forecasts, probably because of a lack of methods. A Bayesian modeling approach (BMA) is adopted, and a flexible model class based on splines is introduced for the mean model. The spline model allows both wind speed and wind direction to be included nonlinearly. The proposed methodology is tested for forecasting hourly maximum 10-min wind speeds based on ensemble forecasts from the European Centre for Medium-Range Weather Forecasts at 204 locations in Norway for lead times from +12 to +108 h. An improvement in the continuous ranked probability score is seen for approximately 85% of the locations using the proposed method compared to standard BMA based on only wind speed forecasts. For moderate-to-strong wind the improvement is substantial, while for low wind speeds there is generally less or no improvement. On average, the improvement is 5%. The proposed methodology can be extended to include more NWP variables in the calibration and can also be applied to other variables.

scholarly journals The importance of wind-blown snow redistribution to snow accumulation on Bellingshausen Sea ice

2011 ◽  
Vol 52 (57) ◽  
pp. 271-278 ◽  
Author(s):  
Katherine C. Leonard ◽  
Ted Maksym
Keyword(s):  
Sea Ice ◽  
Mass Balance ◽  
Snow Accumulation ◽  
Blowing Snow ◽  
Wind Speeds ◽  
Antarctic Sea Ice ◽  
Drifting Snow ◽  
Bellingshausen Sea ◽  
Ice Mass Balance ◽  
High Winds

AbstractSnow distribution is a dominating factor in sea-ice mass balance in the Bellingshausen Sea, Antarctica, through its roles in insulating the ice and contributing to snow-ice production. the wind has long been qualitatively recognized to influence the distribution of snow accumulation on sea ice, but the relative importance of drifting and blowing snow has not been quantified over Antarctic sea ice prior to this study. the presence and magnitude of drifting snow were monitored continuously along with wind speeds at two sites on an ice floe in the Bellingshausen Sea during the October 2007 Sea Ice Mass Balance in the Antarctic (SIMBA) experiment. Contemporaneous precipitation measurements collected on board the RVIB Nathaniel B. Palmer and accumulation measurements by automated ice mass-balance buoys (IMBs) allow us to document the proportion of snowfall that accumulated on level ice surfaces in the presence of high winds and blowing-snow conditions. Accumulation on the sea ice during the experiment averaged <0.01 m w.e. at both IMB sites, during a period when European Centre for Medium-Range Weather Forecasts analyses predicted >0.03 m w.e. of precipitation on the ice floe. Accumulation changes on the ice floe were clearly associated with drifting snow and high winds. Drifting-snow transport during the SIMBA experiment was supply-limited. Using these results to inform a preliminary study using a blowing-snow model, we show that over the entire Southern Ocean approximately half of the precipitation over sea ice could be lost to leads.

Calibration and Cross Validation of Global Ocean Wind Speed Based on Scatterometer Observations

2020 ◽  
Vol 37 (2) ◽  
pp. 279-297 ◽  
Author(s):  
Agustinus Ribal ◽  
Ian R. Young
Keyword(s):  
Wind Speed ◽  
Cross Validation ◽  
Regression Line ◽  
Total Duration ◽  
Global Ocean ◽  
High Wind ◽  
Wind Speeds ◽  
Buoy Data ◽  
Ocean Wind

AbstractGlobal ocean wind speed observed from seven different scatterometers, namely, ERS-1, ERS-2, QuikSCAT, MetOp-A, OceanSat-2, MetOp-B, and Rapid Scatterometer (RapidScat) were calibrated against National Data Buoy Center (NDBC) data to form a consistent long-term database of wind speed and direction. Each scatterometer was calibrated independently against NDBC buoy data and then cross validation between scatterometers was performed. The total duration of all scatterometer data is approximately 27 years, from 1992 until 2018. For calibration purposes, only buoys that are greater than 50 km offshore were used. Moreover, only scatterometer data within 50 km of the buoy and for which the overpass occurred within 30 min of the buoy recording data were considered as a “matchup.” To carry out the calibration, reduced major axis (RMA) regression has been applied where the regression minimizes the size of the triangle formed by the vertical and horizontal offsets of the data point from the regression line and the line itself. Differences between scatterometer and buoy data as a function of time were investigated for long-term stability. In addition, cross validation between scatterometers and independent altimeters was also performed for consistency. The performance of the scatterometers at high wind speeds was examined against buoy and platform measurements using quantile–quantile (Q–Q) plots. Where necessary, corrections were applied to ensure scatterometer data agreed with the in situ wind speed for high wind speeds. The resulting combined dataset is believed to be unique, representing the first long-duration multimission scatterometer dataset consistently calibrated, validated and quality controlled.

Identification of aerodynamic derivatives of bridge decks at high testing wind speed

2018 ◽  
Vol 45 (11) ◽  
pp. 1004-1014
Author(s):  
Quanshun Ding ◽  
Shuanghu Dong ◽  
Zhiyong Zhou
Keyword(s):  
Wind Speed ◽  
Wind Tunnel Test ◽  
Participation Rate ◽  
Single Mode ◽  
High Wind ◽  
Wind Speeds ◽  
Aerodynamic Derivatives ◽  
Vibration Responses ◽  
Mode Extraction ◽  
Derivatives Of

An identification of eight aerodynamic derivatives based on dual-mode and single-mode extraction of system is presented to improve the applicability and accuracy of identification at high testing wind speed. The participation rate to measure the contribution of modes on free-vibration responses is defined and the single-mode extraction is presented to extract the modal parameters of the system at high wind speed. To verify the reliability and applicability of the presented method, the aerodynamic derivatives of a dummy section with known self-excited forces are identified. It is noted that there is a very good agreement between the identified results and the target ones in the range of the low and high wind speeds and the presented method works well after the critical state of flutter. The sectional wind tunnel test of the Tanggu-haihe bridge is performed to identify the aerodynamic derivatives of the deck at the attack angles of −3°, 0°, and 3°.

scholarly journals The importance of blowing snow to halogen-containing aerosol in coastal Antarctica: influence of source region versus wind speed

2018 ◽  
Vol 18 (22) ◽  
pp. 16689-16711 ◽  
Author(s):  
Michael R. Giordano ◽  
Lars E. Kalnajs ◽  
J. Douglas Goetz ◽  
Anita M. Avery ◽  
Erin Katz ◽  
...  
Keyword(s):  
Wind Speed ◽  
Ross Sea ◽  
Source Region ◽  
Ice Cores ◽  
Blowing Snow ◽  
Aerosol Composition ◽  
Austral Spring ◽  
Back Trajectories ◽  
Wind Speeds ◽  
The Impact

Abstract. A fundamental understanding of the processes that control Antarctic aerosols is necessary in determining the aerosol impacts on climate-relevant processes from Antarctic ice cores to clouds. The first in situ observational online composition measurements by an aerosol mass spectrometer (AMS) of Antarctic aerosols were only recently performed during the Two-Season Ozone Depletion and Interaction with Aerosols Campaign (2ODIAC). 2ODIAC was deployed to sea ice on the Ross Sea near McMurdo Station over two field seasons: austral spring–summer 2014 and winter–spring 2015. The results presented here focus on the overall trends in aerosol composition primarily as functions of air masses and local meteorological conditions. The results suggest that the impact of long-range air mass back trajectories on either the absolute or relative concentrations of the aerosol constituents measured by (and inferred from) an AMS at a coastal location is small relative to the impact of local meteorology. However, when the data are parsed by wind speed, two observations become clear. First, a critical wind speed is required to loft snow from the surface, which, in turn, increases particle counts in all measured size bins. Second, elevated wind speeds showed increased aerosol chloride and sodium. Further inspection of the AMS data shows that the increased chloride concentrations have more of a “fast-vaporizing” nature than chloride measured at low wind speed. Also presented are the Cl:Na ratios of snow samples and aerosol filter samples, as measured by ion chromatography, as well as non-chloride aerosol constituents measured by the AMS. Additionally, submicron aerosol iodine and bromine concentrations as functions of wind speed are also presented. The results presented here suggest that aerosol composition in coastal Antarctica is a strong function of wind speed and that the mechanisms determining aerosol composition are likely linked to blowing snow.

scholarly journals A spatial evaluation of high-resolution wind fields from empirical and dynamical modeling in hilly and mountainous terrain

2018 ◽  
Author(s):  
Christoph Schlager ◽  
Gottfried Kirchengast ◽  
Juergen Fuchsberger ◽  
Alexander Kann ◽  
Heimo Truhetz
Keyword(s):  
High Resolution ◽  
Wind Speed ◽  
Climate Model ◽  
Strong Wind ◽  
Wind Fields ◽  
Dynamical Modeling ◽  
Thermally Induced ◽  
Wind Speeds ◽  
Error Measures ◽  
Wind Events

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.

scholarly journals Statistical Downscaling of Gridded Wind Speed Data Using Local Topography

2017 ◽  
Vol 18 (2) ◽  
pp. 335-348 ◽  
Author(s):  
Adam Winstral ◽  
Tobias Jonas ◽  
Nora Helbig
Keyword(s):  
Wind Speed ◽  
Statistical Downscaling ◽  
Surface Wind ◽  
Horizontal Resolution ◽  
Wind Data ◽  
Wind Fields ◽  
Forecast Performance ◽  
Wind Speeds ◽  
Mountain Environments ◽  
High Winds

Abstract Winds, particularly high winds, strongly affect snowmelt and snow redistribution. High winds during rain-on-snow events can lead to catastrophic flooding while strong redistribution events in mountain environments can generate dangerous avalanche conditions. To provide adequate warnings, accurate wind data are required. Yet, mountain wind fields exhibit a high degree of heterogeneity at small spatial lengths that are not resolved by currently available gridded forecast data. Wind data from over 200 stations across Switzerland were used to evaluate two forecast surface wind products (~2- and 7-km horizontal resolution) and develop a statistical downscaling technique to capture these finer-scaled heterogeneities. Wind exposure metrics derived from a 25-m horizontal resolution digital elevation model effectively segregated high, moderate, and low wind speed sites. Forecast performance was markedly compromised and biased low at the exposed sites and biased high at the sheltered, valley sites. It was also found that the variability of predicted wind speeds at these sites did not accurately represent the observed variability. A novel optimization scheme that accounted for local terrain structure while also nudging the forecasted distributions to better match the observed distributions and variability was developed. The resultant statistical downscaling technique notably decreased biases across a range of elevations and exposures and provided a better match to observed wind speed distributions.

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.

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