scholarly journals Using High-Resolution Simulations to Quantify Errors in Radar Estimates of Tornado Intensity

2018 ◽  
Vol 146 (7) ◽  
pp. 2271-2296 ◽  
Author(s):  
Nathan A. Dahl ◽  
David S. Nolan
Keyword(s):  
High Resolution ◽  
Wind Speed ◽  
Wind Direction ◽  
Total Error ◽  
Global Maximum ◽  
Error Type ◽  
Pronounced Increase ◽  
Near Surface ◽  
Temporal Sampling ◽  
Radar Beam

Abstract Observation experiments are performed on a set of high-resolution large-eddy simulations of translating tornado-like vortices. Near-surface Doppler wind measurements are taken by emulating a mobile radar positioned from 1 to 10 km south of each vortex track and conducting single-level scans every 2 s. The departure of each observed gust (wind measurement averaged over two successive scans) from the corresponding true maximum 3-s gust at 10 m AGL (“S10–3s”) is partitioned into error sources associated with resolution volume size, wind direction relative to the radar beam, beam elevation, and temporal sampling. The distributions of each error type are diagrammed as functions of range, observed wind speed, and predicted deviation between the wind direction and the radar beam. The results indicate that the deviation between the wind direction and the radar beam is the predominant source of error in these rapid scan scenarios, although range is also a substantial factor. The median total error is ~10% for small deviation at close range, but it approximately doubles if the range is increased from 1 to 10 km; a more pronounced increase in both the median value and the variance of the total error is seen as the deviation becomes large. Because of this, the underestimate of the global maximum S10–3s approaches 30–40 m s−1 at a longer range, although the global maximum of the time-averaged observed wind speed gives a reasonable approximation of the time-mean maximum S10–3s in many cases. Because of simplifying assumptions and the limited number of cases examined, these results are intended as a baseline for further research.

scholarly journals The Large-eddy Observatory Voitsumra Experiment 2019 (LOVE19) with high-resolution, spatially-distributed observations of air temperature, wind speed, and wind direction from fiber-optic distributed sensing, towers, and ground-based remote sensing

2021 ◽  
Author(s):  
Karl Lapo ◽  
Anita Freundorfer ◽  
Antonia Fritz ◽  
Johann Schneider ◽  
Johannes Olesch ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Boundary Layer ◽  
Wind Speed ◽  
Air Temperature ◽  
Wind Direction ◽  
Fiber Optic ◽  
Layer Structure ◽  
Distributed Sensing ◽  
Near Surface ◽  
Large Eddy

Abstract. The weak-wind Stable Boundary Layer (wwSBL) is poorly described by theory and breaks basic assumptions necessary for observations of turbulence. Understanding the wwSBL requires distributed observations capable of separating between submeso and turbulent scales. To this end, we present the Large Eddy Observatory, Voitsumra Experiment 2019 (LOVE19) which featured 1350 m of fiber optic distributed sensing (FODS) of air temperature and wind speed, as well as an experimental wind direction method, at scales as fine as 1 s and 0.127 m in addition to a suite of point observations of turbulence and ground-based remote sensing. Additionally, flights with a fiber optic cable attached to a tethered balloon provide an unprecedented detailed view of the boundary layer structure with a resolution of 0.254 m and 10 s between 1–200 m height. Two examples are provided demonstrating the unique capabilities of the LOVE19 data for examining boundary layer processes: 1) FODS observations between 1m and ~200 m height during a period of gravity waves propagating across the entire boundary layer and 2) tracking a near-surface, transient submeso structure that causes an intermittent burst of turbulence. All data can be accessed at Zenodo through the DOI https://doi.org/10.5281/zenodo.4312976 (Lapo et al., 2020a).

scholarly journals High resolution modeling of CO<sub>2</sub> over Europe: implications for representation errors of satellite retrievals

2009 ◽  
Vol 9 (5) ◽  
pp. 20599-20630
Author(s):  
D. Pillai ◽  
C. Gerbig ◽  
J. Marshall ◽  
R. Ahmadov ◽  
R. Kretschmer ◽  
...  
Keyword(s):  
High Resolution ◽  
Horizontal Resolution ◽  
Co2 Fluxes ◽  
Modeling Framework ◽  
Global Models ◽  
Near Surface ◽  
Temporal Sampling ◽  
Inverse Models ◽  
Representation Error ◽  
Satellite Retrievals

Abstract. Satellite retrievals for column CO2 with better spatial and temporal sampling are expected to improve the current surface flux estimates of CO2 via inverse techniques. However, the spatial scale mismatch between remotely sensed CO2 and current generation inverse models can induce representation errors, which can cause systematic biases in flux estimates. This study is focused on estimating these representation errors associated with utilization of satellite measurements in global models with a horizontal resolution of about 1 degree or less. For this we used simulated CO2 from the high resolution modeling framework WRF-VPRM, which links CO2 fluxes from a diagnostic biosphere model to a weather forecasting model at 10×10 km2 horizontal resolution. Sub-grid variability of column averaged CO2, i.e. the variability not resolved by global models, reached up to 1.2 ppm. Statistical analysis of the simulation results indicate that orography plays an important role. Using sub-grid variability of orography and CO2 fluxes as well as resolved mixing ratio of CO2, a linear model can be formulated that could explain about 50% of the spatial patterns in the bias component of representation error in column and near-surface CO2 during day- and night-times. These findings give hints for a parameterization of representation error which would allow for the representation error to taken into account in inverse models or data assimilation systems.

High Resolution Wind Fields Retrieved From Spaceborne Synthetic Aperture Radar Images in Comparison to Numerical Models

2002 ◽  
Author(s):  
Jochen Horstmann ◽  
Wolfgang Koch ◽  
Susanne Lehner
Keyword(s):  
High Resolution ◽  
Wind Speed ◽  
Synthetic Aperture Radar ◽  
Wind Direction ◽  
Numerical Models ◽  
Synthetic Aperture ◽  
Wind Fields ◽  
Coastal Regions ◽  
Radar Images ◽  
Aperture Radar

This paper introduces a recently developed algorithm to retrieve high-resolution wind fields over the ocean surface from spaceborne synthetic aperture radar (SAR) data. The algorithm consists of two parts, the first for determining wind direction and the second for wind speed retrieval. Wind directions are extracted from wind induced streaks e.g. from boundary layer rolls, Langmuir cells, or wind shadowing, which are approximately in line with the mean wind direction. Wind speed is derived from the normalized radar cross section (NRCS) and image geometry of the SAR image, together with the local retrieved wind direction. The application of SAR-wind retrieval in coastal regions is demonstrated using data acquired aboard the European satellites ERS-1 and ERS-2 and the Canadian satellite RADARSAT-1. These data allow to measure wind fields of an area of up to 500 km × 500 km with a resolution of up to 200 m. To improve and validate the set-up of numerical high-resolution models in coastal regions SAR-retrieved wind fields offer an unique opportunity. This is shown by comparisons of wind fields measured by SAR to results of the numerical model REMO, HIRLAM and GESIMA.

scholarly journals Spatiotemporal Characteristics of Near-Surface Wind in Shenzhen

2020 ◽  
Vol 12 (2) ◽  
pp. 739 ◽  
Author(s):  
Cheng Liu ◽  
Qinglan Li ◽  
Wei Zhao ◽  
Yuqing Wang ◽  
Riaz Ali ◽  
...  
Keyword(s):  
Wind Speed ◽  
Wind Direction ◽  
Surface Wind ◽  
Prevailing Wind ◽  
Average Wind Speed ◽  
Near Surface ◽  
Average Wind ◽  
Prevailing Wind Direction ◽  
Seasonal Wind ◽  
The Mean

The spatiotemporal characteristics of near-surface wind in Shenzhen were investigated in this study by using hourly observations at 92 automatic weather stations (AWSs) from 2009 to 2018. The results show that during the past 10 years, most of the stations showed a decreasing trend in the annual mean of the 10 min average wind speed (avg-wind) and the mean of the 3 s average wind speed (gust wind). Over half of the decreasing trends at the stations were statistically significant (p < 0.05). Seasonally, the decrease in wind speed was the most severe in spring, followed by autumn, winter, and summer. The distribution of wind speed tends to be greater in the east and coastal areas for both avg-wind and gust wind. From September to March of the following year, the prevailing wind direction in Shenzhen was northerly, and from April to August, the prevailing wind direction was southerly. The seasonal wind speed distribution exhibited two different types, spring–summer type and autumn–winter type, which may be induced by their different prevailing wind directions. The analysis by the empirical orthogonal function (EOF) method confirmed the previous findings that the mean wind speed was decreasing in Shenzhen and that two different seasonal wind speed spatial distribution patterns existed. Such a study could provide references for wind forecasting and risk assessment in the study area.

scholarly journals Quality Control of Surface Wind Observations in Northeastern North America. Part I: Data Management Issues

2018 ◽  
Vol 35 (1) ◽  
pp. 163-182 ◽  
Author(s):  
Etor E. Lucio-Eceiza ◽  
J. Fidel González-Rouco ◽  
Jorge Navarro ◽  
Hugo Beltrami
Keyword(s):  
Quality Control ◽  
Wind Speed ◽  
North America ◽  
Data Management ◽  
Wind Direction ◽  
Measurement Errors ◽  
Surface Wind ◽  
Error Type ◽  
Northeastern North America ◽  
Management Issues

AbstractA quality control (QC) process has been developed and implemented on an observational database of surface wind speed and direction in northeastern North America. The database combines data from 526 land stations and buoys spread across eastern Canada and five adjacent northeastern U.S. states. It combines the observations of three different institutions spanning from 1953 to 2010. The quality of these initial data varies among source institutions. The current QC process is divided into two parts. Part I, described herein, is focused on issues related to data management: issues stemming from data transcription and collection; differences in measurement units and recording times; detection of sequences of duplicated data; unification of calm and true north criteria for wind direction; and detection of physically unrealistic data measurements. As a result, around ~0.1% of wind speed and wind direction records have been identified as erroneous and deleted. The most widespread error type is related to duplications within the same station, but the error type that entails more erroneous data belongs to duplications among different sites. Additionally, the process of data compilation and standardization has had an impact on more than 90% of the records. A companion paper (Part II) deals with a group of errors that are conceptually different, and is focused on detecting measurement errors that relate to temporal consistency and biases in wind speed and direction.

scholarly journals High-Resolution Numerical Modelling of Near-Surface Atmospheric Fields in the Complex Terrain of James Ross Island, Antarctic Peninsula

Atmosphere ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 360
Author(s):  
Michael Matějka ◽  
Kamil Láska ◽  
Klára Jeklová ◽  
Jiří Hošek
Keyword(s):  
Wind Speed ◽  
Air Temperature ◽  
Antarctic Peninsula ◽  
Wind Direction ◽  
Wrf Model ◽  
Lower Altitude ◽  
Near Surface ◽  
James Ross Island ◽  
The Antarctic ◽  
The Impact

The Antarctic Peninsula belongs to the regions of the Earth that have seen the highest increase in air temperature in the past few decades. The warming is reflected in degradation of the cryospheric system. The impact of climate variability and interactions between the atmosphere and the cryosphere can be studied using numerical atmospheric models. In this study, the standard version of the Weather Research and Forecasting (WRF) model was validated on James Ross Island in the northern part of the Antarctic Peninsula. The aim of this study was to verify the WRF model output at 700 m horizontal resolution using air temperature, wind speed and wind direction observations from automatic weather stations on the Ulu Peninsula, the northernmost part of James Ross Island. Validation was carried out for two contrasting periods (summer and winter) in 2019/2020 to assess possible seasonal effects on model accuracy. Simulated air temperatures were in very good agreement with measurements (mean bias −1.7 °C to 1.4 °C). The exception was a strong air temperature inversion during two of the winter days when a significant positive bias occurred at the coastal and lower-altitude locations on the Ulu Peninsula. Further analysis of the WRF estimates showed a good skill in simulating near-surface wind speed with higher correlation coefficients in winter (0.81–0.93) than in summer (0.41–0.59). However, bias and RMSE for wind speed tended to be better in summer. The performance of three WRF boundary layer schemes (MYJ, MYNN, QNSE) was further evaluated. The QNSE scheme was generally more accurate than MYNN and MYJ, but the differences were quite small and varied with time and place. The MYNN and QNSE schemes tended to achieve better wind speed simulation quality than the MYJ scheme. The model successfully captured wind direction, showing only slight differences to the observed values. It was shown that at lower altitudes the performance of the model can vary greatly with time. The model results were more accurate during high wind speed southwestern flow, while the accuracy decreased under weak synoptic-scale forcing, accompanied by an occurrence of mesoscale atmospheric processes.

Morphodynamic processes of blowout on the fixed dune, China

2020 ◽  
Author(s):  
Yanguang Zhou ◽  
Eerdun Hasi
Keyword(s):  
Wind Speed ◽  
Wind Direction ◽  
Meteorological Data ◽  
Image Data ◽  
Convergence Acceleration ◽  
Research Area ◽  
Near Surface ◽  
Airflow Pattern ◽  
Rtk Gps ◽  
The Relationship

&lt;p&gt;Blowout is a common landform on sandy grassland in semi-arid area and part of semi-humid area, and it is the symbol of the activation of fixed dune and the primary manifestation of desertification. This paper selected the south edge of Otingdag Sandy Land as the research area, and used WindSonic and high-precision RTK GPS to measure the airflow and topography of three blowouts with different morphology on the fixed dune. Meanwhile, combining with the image data and meteorological data,we analyzed the morphology evolution process of the three different blowouts and discussed the relationship between airflow and morphology of blowouts. The results showed that the northwest, west and southwest winds were dominant in the study area, and the west wind among them was the most frequent; The average annual wind speed tends to decrease, and the wind direction gradually tends to be stable and unidirectional, which is consistent with the direction of movement of the blowout in this area; From the air inlet to the top of the sand accumulation area, each blowout experienced the process of diffusion deceleration, convergence acceleration, separation deceleration and gradual acceleration along the long axis of the blowout, but the location that highest or lowest wind speed occurred were not the same in different blowout; The relationship between the wind direction and the long axis of blowout determines the airflow pattern inside blowouts. When the airflow diagonally enters the blowout, the airflow pattern tends to be complicated, and the deceleration and acceleration zone in blowout are obviously deviated. After the airflow enters the blowout, the wind speed and direction change obviously, which affects the spatial pattern of erosion or accumulation and further alters the morphology of the blowout. The morphology also in turn reacts on the near-surface airflow, which results in the response and feedback of the morphology and dynamics of the blowout.&lt;/p&gt;

Boundary Layer and Surface Verification of the High-Resolution Rapid Refresh, Version 3

2020 ◽  
Vol 35 (6) ◽  
pp. 2255-2278
Author(s):  
Robert G. Fovell ◽  
Alex Gallagher
Keyword(s):  
Boundary Layer ◽  
High Resolution ◽  
Wind Speed ◽  
Prediction Models ◽  
Weather Prediction ◽  
Potential Temperature ◽  
Ground Level ◽  
Systematic Errors ◽  
Radiosonde Data ◽  
Near Surface

AbstractWhile numerical weather prediction models have made considerable progress regarding forecast skill, less attention has been paid to the planetary boundary layer. This study leverages High-Resolution Rapid Refresh (HRRR) forecasts on native levels, 1-s radiosonde data, and (primarily airport) surface observations across the conterminous United States. We construct temporally and spatially averaged composites of wind speed and potential temperature in the lowest 1 km for selected months to identify systematic errors in both forecasts and observations in this critical layer. We find near-surface temperature and wind speed predictions to be skillful, although wind biases were negatively correlated with observed speed and temperature biases revealed a robust relationship with station elevation. Above ≈250 m above ground level, below which radiosonde wind data were apparently contaminated by processing, biases were small for wind speed and potential temperature at the analysis time (which incorporates sonde data) but became substantial by the 24-h forecast. Wind biases were positive through the layer for both 0000 and 1200 UTC, and morning potential temperature profiles were marked by excessively steep lapse rates that persisted across seasons and (again) exaggerated at higher elevation sites. While the source or cause of these systematic errors are not fully understood, this analysis highlights areas for potential model improvement and the need for a continued and accessible archive of the data that make analyses like this possible.

scholarly journals Using global reanalysis data to quantify and correct airflow distortion bias in shipborne wind speed measurements

2020 ◽  
Vol 13 (6) ◽  
pp. 3487-3506
Author(s):  
Sebastian Landwehr ◽  
Iris Thurnherr ◽  
Nicolas Cassar ◽  
Martin Gysel-Beer ◽  
Julia Schmale
Keyword(s):  
Wind Speed ◽  
Computational Fluid Dynamic ◽  
Wind Direction ◽  
Fluid Dynamic ◽  
Reanalysis Data ◽  
Correction Factors ◽  
Flow Distortion ◽  
Near Surface ◽  
Wind Speeds ◽  
Relative Wind

Abstract. At sea, wind forcing is responsible for the formation and development of surface waves and represents an important source of near-surface turbulence. Therefore, processes related to near-surface turbulence and wave breaking, such as sea spray emission and air–sea gas exchange, are often parameterised with wind speed. Thus, shipborne wind speed measurements provide highly relevant observations. They can, however, be compromised by flow distortion due to the ship's structure and objects near the anemometer that modify the airflow, leading to a deflection of the apparent wind direction and positive or negative acceleration of the apparent wind speed. The resulting errors in the estimated true wind speed can be greatly magnified at low wind speeds. For some research ships, correction factors have been derived from computational fluid dynamic models or through direct comparison with wind speed measurements from buoys. These correction factors can, however, lose their validity due to changes in the structures near the anemometer and, thus, require frequent re-evaluation, which is costly in either computational power or ship time. Here, we evaluate if global atmospheric reanalysis data can be used to quantify the flow distortion bias in shipborne wind speed measurements. The method is tested on data from the Antarctic Circumnavigation Expedition onboard the R/V Akademik Tryoshnikov, which are compared to ERA-5 reanalysis wind speeds. We find that, depending on the relative wind direction, the relative wind speed and direction measurements are biased by −37 % to +22 % and -17∘ to +11∘ respectively. The resulting error in the true wind speed is +11.5 % on average but ranges from −4 % to +41 % (5th and 95th percentile). After applying the bias correction, the uncertainty in the true wind speed is reduced to ±5 % and depends mainly on the average accuracy of the ERA-5 data over the period of the experiment. The obvious drawback of this approach is the potential intrusion of model biases in the correction factors. We show that this problem can be somewhat mitigated when the error propagation in the true wind correction is accounted for and used to weight the observations. We discuss the potential caveats and limitations of this approach and conclude that it can be used to quantify flow distortion bias for ships that operate on a global scale. The method can also be valuable to verify computational fluid dynamic studies of airflow distortion on research vessels.

scholarly journals An NWP Model Intercomparison of Surface Weather Parameters in the European Arctic during the Year of Polar Prediction Special Observing Period Northern Hemisphere 1

2019 ◽  
Vol 34 (4) ◽  
pp. 959-983 ◽  
Author(s):  
Morten Køltzow ◽  
Barbara Casati ◽  
Eric Bazile ◽  
Thomas Haiden ◽  
Teresa Valkonen
Keyword(s):  
High Resolution ◽  
Wind Speed ◽  
The Arctic ◽  
Small Scale ◽  
Limited Area ◽  
Model Intercomparison ◽  
Near Surface ◽  
Surface Weather ◽  
High Resolution Models ◽  
The Impact

AbstractIncreased human activity in the Arctic calls for accurate and reliable weather predictions. This study presents an intercomparison of operational and/or high-resolution models in an attempt to establish a baseline for present-day Arctic short-range forecast capabilities for near-surface weather (pressure, wind speed, temperature, precipitation, and total cloud cover) during winter. One global model [the high-resolution version of the ECMWF Integrated Forecasting System (IFS-HRES)], and three high-resolution, limited-area models [Applications of Research to Operations at Mesoscale (AROME)-Arctic, Canadian Arctic Prediction System (CAPS), and AROME with Météo-France setup (MF-AROME)] are evaluated. As part of the model intercomparison, several aspects of the impact of observation errors and representativeness on the verification are discussed. The results show how the forecasts differ in their spatial details and how forecast accuracy varies with region, parameter, lead time, weather, and forecast system, and they confirm many findings from mid- or lower latitudes. While some weaknesses are unique or more pronounced in some of the systems, several common model deficiencies are found, such as forecasting temperature during cloud-free, calm weather; a cold bias in windy conditions; the distinction between freezing and melting conditions; underestimation of solid precipitation; less skillful wind speed forecasts over land than over ocean; and difficulties with small-scale spatial variability. The added value of high-resolution limited area models is most pronounced for wind speed and temperature in regions with complex terrain and coastlines. However, forecast errors grow faster in the high-resolution models. This study also shows that observation errors and representativeness can account for a substantial part of the difference between forecast and observations in standard verification.

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