scholarly journals Wind speed variability between 10 and 116 m height from the regional reanalysis COSMO-REA6 compared to wind mast measurements over Northern Germany and the Netherlands

2016 ◽  
Vol 13 ◽  
pp. 151-161 ◽  
Author(s):  
Michael Borsche ◽  
Andrea K. Kaiser-Weiss ◽  
Frank Kaspar
Keyword(s):  
Wind Speed ◽  
The Netherlands ◽  
Diurnal Cycle ◽  
Correlation Coefficients ◽  
Wind Fields ◽  
Northern Germany ◽  
Significance Level ◽  
The North ◽  
The Mean ◽  
Regional Reanalysis

Abstract. Hourly and monthly mean wind speed and wind speed variability from the regional reanalysis COSMO-REA6 is analysed in the range of 10 to 116 m height above ground. Comparisons with independent wind mast measurements performed between 2001 and 2010 over Northern Germany over land (Lindenberg), the North Sea (FINO platforms), and The Netherlands (Cabauw) show that the COSMO-REA6 wind fields are realistic and at least as close to the measurements as the global atmospheric reanalyses (ERA20C and ERA-Interim) on the monthly scale. The median wind profiles of the reanalyses were found to be consistent with the observed ones. The mean annual cycles of variability are generally reproduced from 10 up to 116 m in the investigated reanalyses. The mean diurnal cycle is represented qualitatively near the ground by the reanalyses. At 100 m height, there is little diurnal cycle left in the global and regional reanalyses, though a diurnal cycle is still present in the measurements over land. Correlation coefficients between monthly means of the observations and the reanalyses range between 0.92 at 10 m and 0.99 at 116 m, with a slightly higher correlation of the regional reanalyses at Lindenberg at 10 m height which is significant only at a lower than 95 % significance level. Correlations of daily means tend to be higher for the regional reanalysis COSMO-REA6. Increasing temporal resolution further, reduces this advantage of the regional reanalysis. At around 100 m, ERA-Interim yields a higher correlation at Lindenberg and Cabauw, whereas COSMO-REA6 yields a higher correlation at FINO1 and FINO2.

Modulation of the Diurnal Cycle of Warm-Season Precipitation by Short-Wave Troughs

2013 ◽  
Vol 70 (6) ◽  
pp. 1710-1726 ◽  
Author(s):  
John D. Tuttle ◽  
Chris A. Davis
Keyword(s):  
Diurnal Cycle ◽  
North American ◽  
Phase Speed ◽  
Warm Season ◽  
Short Wave ◽  
Short Waves ◽  
The North ◽  
The Mean ◽  
Regional Reanalysis ◽  
Wave Passage

Abstract Traveling deep tropospheric disturbances of wavelengths ~1500 km (short waves) have long been known to play an important role in the initiation and maintenance of warm-season convection. To date, relatively few studies have formally documented the climatology of short waves and their relationship to the diurnal heating cycle, the topography, and the diurnal cycle of precipitation. Those that did had to rely on low-resolution global analyses and often could not track short waves across mountain barriers. In this study, 10 yr of the (32 km) NCEP North American Regional Reanalysis (NARR) are used to objectively identify and track short waves in the North American domain. Statistics of short-wave span, duration, phase speed, latitudinal extent, and locations of preferred intensification/decay are presented. Some of the key findings from the climatology include that the lee (windward) of mountain barriers are preferred regions of intensification (decay) and short waves show little evidence of a diurnal cycle and can pass a given point at any time of the day. The second part of the study focuses on the role that short waves play in modulating the diurnal cycle of propagating convection east of the Rocky Mountains. Depending on the timing of short-wave passage, short waves may either significantly enhance the precipitation above the mean or completely disrupt the normal diurnal cycle, causing precipitation to develop at times and locations where it normally does not. While short waves play an important role in modulating the mean precipitation patterns their role is considered to be secondary in nature. The diurnal precipitation signature is prominent even when short waves are not present.

scholarly journals Different trends between extreme and median surface aerosol extinction coefficients over China inferred from quality controlled visibility data

2017 ◽  
Author(s):  
Jing Li ◽  
Chengcai Li ◽  
Chunsheng Zhao
Keyword(s):  
Northwest China ◽  
Positive Trend ◽  
Median Surface ◽  
Aerosol Extinction ◽  
Significance Level ◽  
The North ◽  
Synoptic Conditions ◽  
The Mean ◽  
Mean Trend ◽  
Year 2000

Abstract. Although the temporal changes of aerosol properties have been widely investigated, the majority focused on the averaged condition without much emphasis on the extremes. However, the latter can be more important in terms of human health and climate change. This study uses a previously validated, quality-controlled visibility dataset to investigate the long-term trends of extreme surface aerosol extinction coefficient (AEC) over China, and compare them with the median trends. Two methods are used to independently evaluate the trends, which arrive at consistent results. The sign of extreme and median trends are generally coherent, whereas their magnitudes show distinct spatial and temporal differences. In the 1980s, an overall positive trend is found throughout China with the extreme trend exceeding the mean trend, except for Northwest China and the North China Plain. In the 1990s, AEC over Northeast and Northwest China starts to decline while the rest of the country still exhibits an increase. The extreme trends continue to dominate in the south while it yields to the mean trend in the north. After year 2000, the extreme trend becomes weaker than the mean trend overall in terms of both the magnitude and significance level. The annual trend can be primarily attributed to winter and fall trends. The results suggest that the decadal changes of pollution in China may be governed by different mechanisms. Synoptic conditions that often result in extreme air quality changes might dominate in the 1980s, whereas emission increase might be the main factor for the 2000s.

scholarly journals Verifying Operational Forecasts of Land–Sea-Breeze and Boundary Layer Mixing Processes

2020 ◽  
Vol 35 (4) ◽  
pp. 1427-1445
Author(s):  
Ewan Short
Keyword(s):  
Boundary Layer ◽  
Diurnal Cycle ◽  
Spatial Scales ◽  
Sea Breeze ◽  
Absolute Error ◽  
Wind Fields ◽  
Mixing Processes ◽  
Relative Contribution ◽  
The Mean ◽  
Diurnal Wind

AbstractForecasters working for Australia’s Bureau of Meteorology (BoM) produce a 7-day forecast in two key steps: first they choose a model guidance dataset to base the forecast on, and then they use graphical software to manually edit these data. Two types of edits are commonly made to the wind fields that aim to improve how the influences of boundary layer mixing and land–sea-breeze processes are represented in the forecast. In this study the diurnally varying component of the BoM’s official wind forecast is compared with that of station observations and unedited model guidance datasets. Coastal locations across Australia over June, July, and August 2018 are considered, with data aggregated over three spatial scales. The edited forecast produces a lower mean absolute error than model guidance at the coarsest spatial scale (over 50 000 km2), and achieves lower seasonal biases over all spatial scales. However, the edited forecast only reduces errors or biases at particular times and locations, and rarely produces lower errors or biases than all model guidance products simultaneously. To better understand physical reasons for biases in the mean diurnal wind cycles, modified ellipses are fitted to the seasonally averaged diurnal wind temporal hodographs. Biases in the official forecast diurnal cycle vary with location for multiple reasons, including biases in the directions that sea breezes approach coastlines, amplitude biases, and disagreement in the relative contribution of sea-breeze and boundary layer mixing processes to the mean diurnal cycle.

scholarly journals Simulation of Snow Water Equivalent (SWE) Using Thermodynamic Snow Models in Québec, Canada

2009 ◽  
Vol 10 (6) ◽  
pp. 1447-1463 ◽  
Author(s):  
A. Langlois ◽  
J. Kohn ◽  
A. Royer ◽  
P. Cliche ◽  
L. Brucker ◽  
...  
Keyword(s):  
Snow Cover ◽  
Snow Water Equivalent ◽  
Meteorological Data ◽  
Regional Scale ◽  
Correlation Coefficients ◽  
Reanalysis Data ◽  
Regional Variability ◽  
The North ◽  
Snow Water ◽  
Regional Reanalysis

Abstract Snow cover plays a key role in the climate system by influencing the transfer of energy and mass between the soil and the atmosphere. In particular, snow water equivalent (SWE) is of primary importance for climatological and hydrological processes and is a good indicator of climate variability and change. Efforts to quantify SWE over land from spaceborne passive microwave measurements have been conducted since the 1980s, but a more suitable method has yet to be developed for hemispheric-scale studies. Tools such as snow thermodynamic models allow for a better understanding of the snow cover and can potentially significantly improve existing snow products at the regional scale. In this study, the use of three snow models [SNOWPACK, CROCUS, and Snow Thermal Model (SNTHERM)] driven by local and reanalysis meteorological data for the simulation of SWE is investigated temporally through three winter seasons and spatially over intensively sampled sites across northern Québec. Results show that the SWE simulations are in agreement with ground measurements through three complete winter seasons (2004/05, 2005/06, and 2007/08) in southern Québec, with higher error for 2007/08. The correlation coefficients between measured and predicted SWE values ranged between 0.72 and 0.99 for the three models and three seasons evaluated in southern Québec. In subarctic regions, predicted SWE driven with the North American Regional Reanalysis (NARR) data fall within the range of measured regional variability. NARR data allow snow models to be used regionally, and this paper represents a first step for the regionalization of thermodynamic multilayered snow models driven by reanalysis data for improved global SWE evolution retrievals.

Quantification of NOX Emissions Based on Car MAX-DOAS Measurements over Beijing and Impacts of Wind Field

2020 ◽  
Author(s):  
Xinghong Cheng
Keyword(s):  
Spatial Distribution ◽  
Wind Speed ◽  
Wind Field ◽  
Meteorological Condition ◽  
Emission Rates ◽  
Wind Fields ◽  
Vertical Column ◽  
Wind Speeds ◽  
South Central ◽  
The Mean

<p>We carried out 14 days of Car MAX-DOAS experiments on the 6th Ring Rd of Beijing in January, September and October, 2014. The tropospheric vertical column densities (VCD) of NO<sub>2</sub> are retrieved and used to estimate the emissions of NO<sub>x</sub>. The offline LAPS-WRF-CMAQ model system is used to simulate wind fields by assimilation of observational data and calculate the NO<sub>2</sub> to NO<sub>x</sub> concentration ratios. The NO<sub>X</sub> emissions in Beijing for different seasons derived from Car MAX-DOAS measurements are compared with the multi-resolution emission inventory in China for 2012 (MEIC 2012), and impacts of wind field on estimated emissions and its uncertainties are also investigated. Results show that the NO<sub>2</sub> VCD is higher in January than other two months and it is typically larger at the southern parts of the 6th Ring Road than the northern parts of it. Wind field has obvious impacts on the spatial distribution of NO<sub>2</sub> VCD, and the mean NO<sub>2</sub> VCD with south wind at most sampling points along the 6th Ring Rd is higher than north wind. The journey-to-journey variation pattern of estimated NO<sub>X</sub> emissions rates (E<sub>NOX</sub>) is consistent with that of the NO<sub>2</sub> VCD, and E<sub>NOX </sub>is mainly determined by the NO2 VCD. In addition, the journey-to-journey E<sub>NOX</sub> in the same month is different and it is affected by wind speed, the ratio of NO<sub>2</sub> and NOx concentration and the decay rate of NO<sub>X</sub> from the emission sources to measured positions under different meteorological condition. The E<sub>NOX</sub> ranges between 6.46×10<sup>25</sup> and 50.05×10<sup>25</sup> molec s<sup>-1</sup>. The averaged E<sub>NOX</sub> during every journey in January, September and October are respectively 35.87×10<sup>25</sup>, 20.34×10<sup>25</sup>, 8.96×10<sup>25</sup> molec s<sup>-1</sup>. The estimated E<sub>NOX</sub> after removing the simulated error of wind speed and observed deviation of NO<sub>2</sub> VCD are found to be mostly closer to the MEIC 2012, but sometimes E<sub>NOX </sub>is lower or higher and it indicates that the MEIC 2012 might be overestimate or underestimate the true emissions. The estimated E<sub>NOX</sub> on January 27 and September 19 are obviously higher than other journeys in the same month because the mean NO<sub>2</sub> VCD and Leighton ratio during these two periods are larger, and corresponding wind speeds are smaller. Additionally, because south wind may affect the spatial distribution of mean NO<sub>2</sub> VCD in Beijing which is downwind of south-central regions of Hebei province with high source emission rates, the uncertainty of the estimated E<sub>NOX</sub> with south wind will be increased.</p>

Wind tunnel tests on the characteristics of wind fields over a simplified gorge

2016 ◽  
Vol 20 (10) ◽  
pp. 1599-1611 ◽  
Author(s):  
Peng Hu ◽  
Yongle Li ◽  
Yan Han ◽  
CS Cai ◽  
Guoji Xu
Keyword(s):  
Wind Speed ◽  
Wind Tunnel ◽  
Wind Direction ◽  
Wind Field ◽  
Small Range ◽  
Wind Fields ◽  
Wind Speeds ◽  
Mean Wind Speed ◽  
Wind Characteristics ◽  
The Mean

Characteristics of wind fields over the gorge or valley terrains are becoming more and more important to the structural wind engineering. However, the studies on this topic are very limited. To obtain the fundamental characteristics information about the wind fields over a typical gorge terrain, a V-shaped simplified gorge, which was abstracted from some real deep-cutting gorges where long-span bridges usually straddle, was introduced in the present wind tunnel studies. Then, the wind characteristics including the mean wind speed, turbulence intensity, integral length scale, and the wind power spectrum over the simplified gorge were studied in a simulated atmospheric boundary layer. Furthermore, the effects of the oncoming wind field type and oncoming wind direction on these wind characteristics were also investigated. The results show that compared with the oncoming wind, the wind speeds at the gorge center become larger, but the turbulence intensities and the longitudinal integral length scales become smaller. Generally, the wind fields over the gorge terrain can be approximately divided into two layers, that is, the gorge inner layer and the gorge outer layer. The different oncoming wind field types have remarkable effects on the mean wind speed ratios near the ground. When the angle between the oncoming wind and the axis of the gorge is in a certain small range, such as smaller than 10°, the wind fields are very close to those associated with the wind direction of 0°. However, when the angle is in a larger range, such as larger than 20°, the wind fields in the gorge will significantly change. The research conclusions can provide some references for civil engineering practices regarding the characteristics of wind fields over the real gorge terrains.

Structure of microseismic waves: estimation of direction of approach by comparison of vertical and horizontal components

1954 ◽  
Vol 223 (1152) ◽  
pp. 96-111 ◽  
Keyword(s):  
Rayleigh Waves ◽  
Vertical Component ◽  
Correlation Coefficients ◽  
Love Waves ◽  
The North ◽  
Wave Interference ◽  
Rayleigh And Love Waves ◽  
The Mean ◽  
East West ◽  
Phase Differences

Analysis of microseisms recorded at Kew Observatory on 8 to 10 October 1951 affords further confirmation of the wave-interference theory of microseism generation, and allows those of 8 to 10 October to be attributed to a fast-moving depression between the Azores and Iceland. Although the bearing of the microseism-generating area changes by more than 90° during the period investigated, there is no appreciable difference in the ratio of the mean ampli­tudes of the north-south and east-west horizontal components as would be expected if the microseisms consisted entirely of Rayleigh waves. An investigation of the phase differences between the three components, using Lee’s method, suggests that the microseisms consist of Rayleigh and Love waves in comparable proportions. Making use of this assumption, the vertical component, which is not affected by the Love waves, is correlated with the two horizontal components with an electronic correlating device, and the bearing of the microseism area can be deduced from the correlation coefficients. The calculated bearings agree reasonably well with those obtained from the meteorological charts. The bearing of a storm on 12 to 15 November 1945, studied in a previous paper, was also calculated satisfactorily.

scholarly journals Thermal, pressure and wind fields at ground level in the area of the Italian base at Terra Nova Bay, Victoria Land, Antarctica, as observed by a network of automatic weather stations

1996 ◽  
Vol 14 (10) ◽  
pp. 1088-1094 ◽  
Author(s):  
E. Cogliani ◽  
G. Abbate ◽  
S. Racalbuto
Keyword(s):  
Wind Speed ◽  
Coastal Region ◽  
Ground Level ◽  
Katabatic Wind ◽  
Wind Fields ◽  
The North ◽  
Terra Nova Bay ◽  
Spatial Configurations ◽  
Weather Stations ◽  
Terra Nova

Abstract. Ground temperature, pressure and wind speed monthly averages in the area of the Italian Station at Terra Nova Bay, Antarctica, were analyzed for the period 1987–1991 by means of a network of nine AWS (automatic weather stations). Spatial configurations of temperature show a well-defined, relatively warm island in the area of Terra Nova Bay, between Drygalsky and Campbell ice tongues, throughout the year. A second warm island is present to the north along the coast, between Aviator and Mariner ice tongues, for most of the year. From February to March a rapid drop in temperature is observed at all stations. A strong thermal gradient develops during February, March, April and October, November, December, between the coastal region and inner highlands. The baric configuration follows the elevation of the area. Annual average pressure and temperature as functions of stations altitude show linear trends. Severe katabatic wind episodes are recorded at all stations, with wind speed exceeding 25 m s–1 and direction following the orographic features of the inner areas. Co-occurrences of these episodes were observed for stations located along stream lines of cold air drainage. The autocorrelation function of maximum wind speed time series shows wind persistence of 2–3 days and wind periodicity of about one week.

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>

scholarly journals Data Clustering Reveals Climate Impacts on Local Wind Phenomena

2012 ◽  
Vol 51 (8) ◽  
pp. 1547-1557 ◽  
Author(s):  
Andrew Clifton ◽  
Julie K. Lundquist
Keyword(s):  
Wind Speed ◽  
Pressure Gradient ◽  
Climate Impacts ◽  
Climate Indices ◽  
Local Conditions ◽  
Climate Oscillations ◽  
The North ◽  
Westerly Flow ◽  
Mean Wind Speed ◽  
The Mean

AbstractThe authors demonstrate the utility of k-means clustering for identifying relationships between winds at turbine heights and climate oscillations, thereby developing a method suited for predicting the impacts of climate change on wind resources. Fourteen years of data from an 80-m tower at the National Wind Technology Center (NWTC) in Colorado have been reduced to four dominant flow phenomena using k-means clustering. At this location, this method identifies two clusters of westerly inflow (strong and weak), another cluster of flow from the north, and one of flow from the south. Similar clusters are found for the data at all heights on the tower, and each follow distinct seasonal cycles. Time series of each cluster, as well as the mean wind speed at the NWTC, are retained for comparison with climate oscillations along with the local 500-hPa pressure gradient. The mean wind speed in the surface layer is strongly correlated with the local north–south pressure gradient. The frequency of strong westerly flow is also negatively correlated with the Niño-3.4 index, whereas weaker westerly winds are negatively correlated with the Pacific–North American pattern (PNA) and Arctic Oscillation (AO). Northerly winds at the NWTC did not strongly correlate with any of the investigated climate indices (AO, PNA, and Niño-3.4). These northerly winds occur more frequently in the summer months, suggesting that these winds are more influenced by local conditions than by mesoscale forcing. This method of identifying clusters in wind data allows objective identification of wind phenomena that may benefit the deployment of wind turbines, for example, in choosing combinations of wind speed and direction to investigate for turbine siting.

Sign in / Sign up

Export Citation Format

Share Document