scholarly journals Prediction of Near-Surface Variables at Independent Locations from a Bias-Corrected Ensemble Forecasting System

2006 ◽  
Vol 134 (11) ◽  
pp. 3415-3424 ◽  
Author(s):  
Nusrat Yussouf ◽  
David J. Stensrud
Keyword(s):  
New England ◽  
Near Surface ◽  
Wind Speeds ◽  
Dewpoint Temperature ◽  
Model Domain ◽  
Oklahoma Mesonet ◽  
Independent Observations ◽  
Forecasting System ◽  
Surface Station ◽  
Forecast Time

Abstract The ability of a multimodel short-range bias-corrected ensemble (BCE) forecasting system, created as part of NOAA’s New England High Resolution Temperature Program during the summer of 2004, to obtain accurate predictions of near-surface variables at independent locations within the model domain is explored. The original BCE approach produces bias-corrected forecasts only at National Weather Service (NWS) observing surface station locations. To extend this approach to obtain bias-corrected forecasts at any given location, an extended BCE technique is developed and applied to the independent observations provided by the Oklahoma Mesonet. First, a Cressman weighting scheme is used to interpolate the bias values of 2-m temperature, 2-m dewpoint temperature, and 10-m wind speeds calculated from the original BCE approach at the NWS observation station locations to the Oklahoma Mesonet locations. These bias values are then added to the raw numerical model forecasts bilinearly interpolated to this same specified location. This process is done for each forecast member within the ensemble and at each forecast time. It is found that the performance of the extended BCE is very competitive with the original BCE approach across the state of Oklahoma. Therefore, a simple postprocessing scheme like the extended BCE system can be used as part of an operational forecasting system to provide reasonably accurate predictions of near-surface variables at any location within the model domain.

scholarly journals Comparison of regional and global reanalysis near-surface winds with station observations over Germany

2015 ◽  
Vol 12 (1) ◽  
pp. 187-198 ◽  
Author(s):  
A. K. Kaiser-Weiss ◽  
F. Kaspar ◽  
V. Heene ◽  
M. Borsche ◽  
D. G. H. Tan ◽  
...  
Keyword(s):  
Information Source ◽  
Surface Wind ◽  
Wind Fields ◽  
Near Surface ◽  
Wind Speeds ◽  
Energy Applications ◽  
The North ◽  
Independent Observations ◽  
Spatio Temporal ◽  
The North Atlantic Oscillation

Abstract. Reanalysis near-surface wind fields from multiple reanalyses are potentially an important information source for wind energy applications. Inter-comparing reanalyses via employing independent observations can help to guide users to useful spatio-temporal scales. Here we compare the statistical properties of wind speeds observed at 210 traditional meteorological stations over Germany with the reanalyses' near-surface fields, confining the analysis to the recent years (2007 to 2010). In this period, the station time series in Germany can be expected to be mostly homogeneous. We compare with a regional reanalysis (COSMO-REA6) and two global reanalyses, ERA-Interim and ERA-20C. We show that for the majority of the stations, the Weibull parameters of the daily mean wind speed frequency distribution match remarkably well with the ones derived from the reanalysis fields. High correlations (larger than 0.9) can be found between stations and reanalysis monthly mean wind speeds all over Germany. Generally, the correlation between the higher resolved COSMO-REA6 wind fields and station observations is highest, for both assimilated and non-assimilated (i.e., independent) observations. As expected from the lower spatial resolution and reduced amount of data assimilated into ERA-20C, the correlation of monthly means decreases somewhat relative to the other reanalyses (in our investigated period of 2007 to 2010). Still, the inter-annual variability connected to the North Atlantic Oscillation (NAO) found in the reanalysis surface wind anomalies is in accordance with the anomalies recorded by the stations. We discuss some typical examples where differences are found, e.g., where the mean wind distributions differ (probably related to either height or model topography differences) and where the correlations break down (because of unresolved local topography) which applies to a minority of stations. We also identified stations with homogeneity problems in the reported station values, demonstrating how reanalyses can be applied to support quality control for the observed station data. Finally, as a demonstration of concept, we discuss how comparing feedback files of the different reanalyses can guide users to useful scales of variability.

scholarly journals Projected Changes in European and North Atlantic Seasonal Wind Climate Derived from CMIP5 Simulations

2019 ◽  
Vol 32 (19) ◽  
pp. 6467-6490 ◽  
Author(s):  
Kimmo Ruosteenoja ◽  
Timo Vihma ◽  
Ari Venäläinen
Keyword(s):  
North Atlantic ◽  
Climate Models ◽  
Global Climate ◽  
Arctic Sea Ice ◽  
Global Climate Models ◽  
Near Surface ◽  
Wind Speeds ◽  
The North ◽  
Seasonal Wind ◽  
Projected Changes

Abstract Future changes in geostrophic winds over Europe and the North Atlantic region were studied utilizing output data from 21 CMIP5 global climate models (GCMs). Changes in temporal means, extremes, and the joint distribution of speed and direction were considered. In concordance with previous research, the time mean and extreme scalar wind speeds do not change pronouncedly in response to the projected climate change; some degree of weakening occurs in the majority of the domain. Nevertheless, substantial changes in high wind speeds are identified when studying the geostrophic winds from different directions separately. In particular, in northern Europe in autumn and in parts of northwestern Europe in winter, the frequency of strong westerly winds is projected to increase by up to 50%. Concurrently, easterly winds become less common. In addition, we evaluated the potential of the GCMs to simulate changes in the near-surface true wind speeds. In ocean areas, changes in the true and geostrophic winds are mainly consistent and the emerging differences can be explained (e.g., by the retreat of Arctic sea ice). Conversely, in several GCMs the continental wind speed response proved to be predominantly determined by fairly arbitrary changes in the surface properties rather than by changes in the atmospheric circulation. Accordingly, true wind projections derived directly from the model output should be treated with caution since they do not necessarily reflect the actual atmospheric response to global warming.

scholarly journals Local Characteristics of the Nocturnal Boundary Layer in Response to External Pressure Forcing

2017 ◽  
Vol 56 (11) ◽  
pp. 3035-3047 ◽  
Author(s):  
Steven J. A. van der Linden ◽  
Peter Baas ◽  
J. Antoon van Hooft ◽  
Ivo G. S. van Hooijdonk ◽  
Fred C. Bosveld ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Wind Speed ◽  
Stable Boundary Layer ◽  
Dynamical Behavior ◽  
Geostrophic Wind ◽  
External Pressure ◽  
Near Surface ◽  
Stable Boundary ◽  
Wind Speeds ◽  
Turbulent Characteristics

AbstractGeostrophic wind speed data, derived from pressure observations, are used in combination with tower measurements to investigate the nocturnal stable boundary layer at Cabauw, the Netherlands. Since the geostrophic wind speed is not directly influenced by local nocturnal stability, it may be regarded as an external forcing parameter of the nocturnal stable boundary layer. This is in contrast to local parameters such as in situ wind speed, the Monin–Obukhov stability parameter (z/L), or the local Richardson number. To characterize the stable boundary layer, ensemble averages of clear-sky nights with similar geostrophic wind speeds are formed. In this manner, the mean dynamical behavior of near-surface turbulent characteristics and composite profiles of wind and temperature are systematically investigated. The classification is found to result in a gradual ordering of the diagnosed variables in terms of the geostrophic wind speed. In an ensemble sense the transition from the weakly stable to very stable boundary layer is more gradual than expected. Interestingly, for very weak geostrophic winds, turbulent activity is found to be negligibly small while the resulting boundary cooling stays finite. Realistic numerical simulations for those cases should therefore have a comprehensive description of other thermodynamic processes such as soil heat conduction and radiative transfer.

scholarly journals Digital data set of generalized lithogeochemical characteristics of near-surface bedrock in the New England Coastal Basins

Fact Sheet ◽  
2002 ◽  
Author(s):  
Denise L. Montgomery ◽  
G.R. Robinson ◽  
J.D. Ayotte ◽  
S.M. Flanagan ◽  
K.W. Robinson
Keyword(s):  
New England ◽  
Digital Data ◽  
Data Set ◽  
Near Surface ◽  
Coastal Basins

scholarly journals MAX-DOAS observations of the total atmospheric water vapour column and comparison with independent observations

2013 ◽  
Vol 6 (1) ◽  
pp. 131-149 ◽  
Author(s):  
T. Wagner ◽  
M. O. Andreae ◽  
S. Beirle ◽  
S. Dörner ◽  
K. Mies ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Water Vapour ◽  
Satellite Observations ◽  
Shielding Effect ◽  
Optical Absorption Spectroscopy ◽  
Atmospheric Water ◽  
Near Surface ◽  
Atmospheric Water Vapour ◽  
Independent Observations ◽  
Good Agreement

Abstract. We developed an algorithm for the retrieval of the atmospheric water vapour column from Multi-AXis Differential Optical Absorption Spectroscopy (MAX-DOAS) observations in the yellow and red spectral range. The retrieval is based on the so-called geometric approximation and does not depend on explicit a priori information for individual observations, extensive radiative transfer simulations, or the construction of large look-up tables. Disturbances of the radiative transfer due to aerosols and clouds are simply corrected using the simultaneously measured absorptions of the oxygen dimer, O4. We applied our algorithm to MAX-DOAS observations made at the Max Planck Institute for Chemistry in Mainz, Germany, from March to August 2011, and compared the results to independent observations. Good agreement with Aerosol Robotic Network (AERONET) and European Centre for Medium-Range Weather Forecasting (ECMWF) H2O vertical column densities (VCDs) is found, while the agreement with satellite observations is less good, most probably caused by the shielding effect of clouds for the satellite observations. Good agreement is also found with near-surface in situ observations, and it was possible to derive average daily H2O scale heights (between 1.5 km and 3 km). MAX-DOAS measurements use cheap and simple instrumentation and can be run automatically. One important advantage of our algorithm is that the H2O VCD can be retrieved even under cloudy conditions (except clouds with very high optical thickness).

Elliptic Airfoil Stall Analysis With Trailing Edge Slots

2010 ◽  
Author(s):  
Jonathan Kweder ◽  
Mary Ann Clarke ◽  
James E. Smith
Keyword(s):  
Lift Coefficient ◽  
Leading Edge ◽  
Surface Velocity ◽  
Circulation Control ◽  
West Virginia University ◽  
Trailing Edge ◽  
Near Surface ◽  
Wind Speeds ◽  
Edge Location ◽  
Stall Angle

Circulation control (CC) is a high-lift methodology that can be used on a variety of aerodynamic applications. This technology has been in the research and development phase for over sixty years primarily for fixed wing aircraft where the early models were referred to as “blown flaps”. Circulation control works by increasing the near surface velocity of the airflow over the leading edge and/or trailing edge of a lifting surface This phenomenon keeps the boundary layer jet attached to the wing surface thus increasing the lift generated on the surface. The circulation control airflow adds energy to the lift force through conventional airfoil lift production and by altering the circulation of stream lines around the airfoil. For this study, a 10:1 aspect ratio elliptical airfoil with a chord length of 11.8 inches and a span of 31.5 inches was inserted into the West Virginia University Closed Loop Wind Tunnel and was tested at varying wind speeds (80, 100, and 120 feet per second), angle of attack (zero to sixteen degrees), and blowing coefficients, ranging from 0.0006 to 0.0127 depending on plenum pressure. By comparing the non-circulation controlled wing with the active circulation control data, a trend was found as to the influence of circulation control on the stall characteristics of the wing for trailing edge active control. For this specific case, when the circulation control is in use on the 10:1 elliptical airfoil, the stall angle decreased, from eight degrees to six degrees, while providing a 70% increase in lift coefficient. It should be noted that due to the trailing edge location of the circulation control exit jet, a “virtual” camber is created with the free stream air adding length to the overall airfoil. Due to this phenomena, the actual stall angle measured increased from eight degrees on the un-augmented airfoil, to a maximum of twelve degrees.

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>

Data Sets

2013 ◽  
Author(s):  
James B. Elsner ◽  
Thomas H. Jagger
Keyword(s):  
Model Building ◽  
Careful Analysis ◽  
Logical Structure ◽  
Fortran Program ◽  
Data Sets ◽  
Data Set ◽  
Near Surface ◽  
Wind Speeds ◽  
The North ◽  
The One

Hurricane data originate from careful analysis of past storms by operational meteorologists. The data include estimates of the hurricane position and intensity at 6-hourly intervals. Information related to landfall time, local wind speeds, damages, and deaths, as well as cyclone size, are included. The data are archived by season. Some effort is needed to make the data useful for hurricane climate studies. In this chapter, we describe the data sets used throughout this book. We show you a work flow that includes importing, interpolating, smoothing, and adding attributes. We also show you how to create subsets of the data. Code in this chapter is more complicated and it can take longer to run. You can skip this material on first reading and continue with model building in Chapter 7. You can return here when you have an updated version of the data that includes the most recent years. Most statistical models in this book use the best-track data. Here we describe these data and provide original source material. We also explain how to smooth and interpolate them. Interpolations are needed for regional hurricane analyses. The best-track data set contains the 6-hourly center locations and intensities of all known tropical cyclones across the North Atlantic basin, including the Gulf of Mexico and Caribbean Sea. The data set is called HURDAT for HURricane DATa. It is maintained by the U.S. National Oceanic and Atmospheric Administration (NOAA) at the National Hurricane Center (NHC). Center locations are given in geographic coordinates (in tenths of degrees) and the intensities, representing the one-minute near-surface (∼10 m) wind speeds, are given in knots (1 kt = .5144 m s−1) and the minimum central pressures are given in millibars (1 mb = 1 hPa). The data are provided in 6-hourly intervals starting at 00 UTC (Universal Time Coordinate). The version of HURDAT file used here contains cyclones over the period 1851 through 2010 inclusive. Information on the history and origin of these data is found in Jarvinen et al (1984). The file has a logical structure that makes it easy to read with a FORTRAN program. Each cyclone contains a header record, a series of data records, and a trailer record.

scholarly journals Seasonally Resolved Distributional Trends of North American Temperatures Show Contraction of Winter Variability

2017 ◽  
Vol 30 (3) ◽  
pp. 1139-1157 ◽  
Author(s):  
Andrew Rhines ◽  
Karen A. McKinnon ◽  
Martin P. Tingley ◽  
Peter Huybers
Keyword(s):  
North American ◽  
Daily Maximum ◽  
Spatial Covariance ◽  
Near Surface ◽  
Online Tool ◽  
Dipole Structure ◽  
Uncertainty Estimates ◽  
Winter Temperatures ◽  
Surface Station ◽  
The Mean

Abstract There is considerable interest in determining whether recent changes in the temperature distribution extend beyond simple shifts in the mean. The authors present a framework based on quantile regression, wherein trends are estimated across percentiles. Pointwise trends from surface station observations are mapped into continuous spatial fields using thin-plate spline regression. This procedure allows for resolving spatial dependence of distributional trends, providing uncertainty estimates that account for spatial covariance and varying station density. The method is applied to seasonal near-surface temperatures between 1979 and 2014 to unambiguously assess distributional changes in the densely sampled North American region. Strong seasonal differences are found, with summer trends exhibiting significant warming throughout the domain with little distributional dependence, while the spatial distribution of spring and fall trends show a dipole structure. In contrast, the spread between the 95th and 5th percentile in winter has decreased, with trends of −0.71° and −0.85°C decade−1, respectively, for daily maximum and minimum temperature, a contraction that is statistically significant over 84% of the domain. This decrease in variability is dominated by warming of the coldest days, which has outpaced the median trend by approximately a factor of 4. Identical analyses using ERA-Interim and NCEP-2 yield consistent estimates for winter (though not for other seasons), suggesting that reanalyses can be reliably used for relating winter trends to circulation anomalies. These results are consistent with Arctic-amplified warming being strongest in winter and with the influence of synoptic-scale advection on winter temperatures. Maps for all percentiles, seasons, and datasets are provided via an online tool.

scholarly journals At What Time of Day Do Daily Extreme Near-Surface Wind Speeds Occur?

2014 ◽  
Vol 27 (11) ◽  
pp. 4226-4244 ◽  
Author(s):  
Robert Fajber ◽  
Adam H. Monahan ◽  
William J. Merryfield
Keyword(s):  
Extreme Values ◽  
Mechanistic Model ◽  
Surface Wind ◽  
Time Of Day ◽  
Near Surface ◽  
Wind Speeds ◽  
Boundary Layer Processes ◽  
Early Afternoon ◽  
Extreme Wind ◽  
Extreme Wind Speeds

Abstract The timing of daily extreme wind speeds from 10 to 200 m is considered using 11 yr of 10-min averaged data from the 213-m tower at Cabauw, the Netherlands. This analysis is complicated by the tendency of autocorrelated time series to take their extreme values near the beginning or end of a fixed window in time, even when the series is stationary. It is demonstrated that a simple averaging procedure using different base times to define the day effectively suppresses this “edge effect” and enhances the intrinsic nonstationarity associated with diurnal variations in boundary layer processes. It is found that daily extreme wind speeds at 10 m are most likely in the early afternoon, whereas those at 200 m are most likely in between midnight and sunrise. An analysis of the joint distribution of the timing of extremes at these two altitudes indicates the presence of two regimes: one in which the timing is synchronized between these two layers, and the other in which the occurrence of extremes is asynchronous. These results are interpreted physically using an idealized mechanistic model of the surface layer momentum budget.

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