scholarly journals Verification of Near Surface Wind Patterns in Germany using Clear Air Radar Echoes

2021 ◽  
Author(s):  
Sebastian Buschow ◽  
Petra Friederichs
Keyword(s):  
Spatial Scales ◽  
Surface Wind ◽  
Horizontal Wind ◽  
Data Sets ◽  
Grey Zone ◽  
Wind Fields ◽  
Validation Data ◽  
Near Surface ◽  
Radar Echoes ◽  
Wind Patterns

Abstract. The verification of high-resolution meteorological models requires highly resolved validation data and appropriate tools of analysis. While much progress has been made in the case of precipitation, wind fields have received less attention, largely due to a lack of spatial measurements. Clear-sky radar echoes could be an unexpected part of the solution by affording us an indirect look at horizontal wind patterns: Regions of horizontal convergence attract non-meteorological scatterers such as insects; their concentration visualizes the structure of the convergence field. Using a two-dimensional wavelet transform, this study demonstrates how divergences and reflectivities can be quantitatively compared in terms of their spatial scale, (horizontal) anisotropy and direction. A long-term validation of the highly resolved regional reanalysis COSMO-REA2 against the German radar composite RADOLAN shows surprisingly close agreement. Despite theoretically predicted problems with simulations in or near the ‘grey-zone’ of turbulence, COSMO-REA2 is shown to produce a realistic diurnal cycle of the spatial scales larger than 8 km. In agreement with the literature, the orientation of the patterns in both data-sets closely follows the mean wind direction. Conversely, an analysis of the horizontal anisotropy reveals that the model has an unrealistic tendency towards highly linear, roll like patterns early in the day.

Frequency of Mountain Waves Over Kanto Area Revealed by Imaging Observations of OH Airglow

2021 ◽  
Author(s):  
Satoshi Ishii ◽  
Yoshihiro Tomikawa ◽  
Masahiro Okuda ◽  
Hidehiko Suzuki
Keyword(s):  
Spatial Scales ◽  
Lower Atmosphere ◽  
Horizontal Wind ◽  
Leeward Side ◽  
Mountainous Areas ◽  
Wind Fields ◽  
Mountain Waves ◽  
The World ◽  
Geostationary Meteorological Satellite ◽  
Good Proxy

Abstract Imaging observations of OH airglow were conducted at Meiji University, Japan (IN, mE), from May 2018 to December 2019. Mountainous areas, including Mt. Fuji, are located to the west of the imager, and westerly winds are dominant in the lower atmosphere throughout the year. Mountain waves (MWs) are generated on the leeward sides of mountains and occasionally propagate to the upper atmosphere. However, during the observation period (about 1 year and 8 months), only four possible MW events were identified. Based on previous reports, this incidence is considerably lower than expected. There are two possible reasons for the low incidence of MW events: (1) The frequency of MW excitation is small in the lower layers of the atmosphere, and/or (2) MWs do not propagate easily to the upper mesosphere due to background wind conditions. This study verified the likelihood of the former case. Under over-mountain airflow conditions, wavy clouds are often generated on the leeward side. Since over-mountain airflow is essential for the excitation of MWs, the frequency of wavy clouds in the lower atmosphere can be regarded as a measure of the occurrence of MWs. The frequency and spatial distribution of MWs around Japan were investigated by detecting the wavy clouds from color images taken by the Himawari-8 geostationary meteorological satellite (GSM-8) for one year in 2018. The wavy clouds were detected on more than 70 days a year around the Tohoku region, but just 20 days a year around Mt. Fuji. This suggests that few MWs are generated around Mt. Fuji. The differences between these two regions were examined focusing on the relationship between the local topography and dominant horizontal wind fields in the lower atmosphere. Specifically, the findings showed that the angle between the dominant horizontal wind direction and the orientation of the mountain ridge is a good proxy of the occurrence of wavy clouds, i.e., excitation of MWs in mountainous areas. We have also applied this proxy to topography in other areas of the world to investigate areas where MWs would be occurring frequently. Finally, we discuss the likelihood of "MW hotspots" at various spatial scales in the world.

scholarly journals Assessing the Impact of Changes in Land Surface Conditions on WRF Predictions in Arid Regions

2020 ◽  
Vol 21 (12) ◽  
pp. 2829-2853 ◽  
Author(s):  
Marouane Temimi ◽  
Ricardo Fonseca ◽  
Narendra Nelli ◽  
Michael Weston ◽  
Mohan Thota ◽  
...  
Keyword(s):  
Eddy Covariance ◽  
Soil Texture ◽  
Land Surface ◽  
Surface Wind ◽  
Surface Fluxes ◽  
Abu Dhabi ◽  
Horizontal Wind ◽  
Cold Bias ◽  
Near Surface ◽  
The Impact

AbstractA thorough evaluation of the Weather Research and Forecasting (WRF) Model is conducted over the United Arab Emirates, for the period September 2017–August 2018. Two simulations are performed: one with the default model settings (control run), and another one (experiment) with an improved representation of soil texture and land use land cover (LULC). The model predictions are evaluated against observations at 35 weather stations, radiosonde profiles at the coastal Abu Dhabi International Airport, and surface fluxes from eddy-covariance measurements at the inland city of Al Ain. It is found that WRF’s cold temperature bias, also present in the forcing data and seen almost exclusively at night, is reduced when the surface and soil properties are updated, by as much as 3.5 K. This arises from the expansion of the urban areas, and the replacement of loamy regions with sand, which has a higher thermal inertia. However, the model continues to overestimate the strength of the near-surface wind at all stations and seasons, typically by 0.5–1.5 m s−1. It is concluded that the albedo of barren/sparsely vegetated regions in WRF (0.380) is higher than that inferred from eddy-covariance observations (0.340), which can also explain the referred cold bias. At the Abu Dhabi site, even though soil texture and LULC are not changed, there is a small but positive effect on the predicted vertical profiles of temperature, humidity, and horizontal wind speed, mostly between 950 and 750 hPa, possibly because of differences in vertical mixing.

scholarly journals Evaluation of a Regional Reanalysis and ERA-Interim over East Asia Using In Situ Observations during 2013–14

2017 ◽  
Vol 56 (10) ◽  
pp. 2821-2844 ◽  
Author(s):  
Eun-Gyeong Yang ◽  
Hyun Mee Kim
Keyword(s):  
Relative Humidity ◽  
East Asia ◽  
Geopotential Height ◽  
Spatial Scales ◽  
Weather Prediction ◽  
Surface Wind ◽  
Lower Troposphere ◽  
Near Surface ◽  
Skill Scores ◽  
Regional Reanalysis

AbstractIn this study, the East Asia Regional Reanalysis (EARR) is developed for the period 2013–14 and characteristics of the EARR are examined in comparison with ERA-Interim (ERA-I) reanalysis. The EARR is based on the Unified Model with 12-km horizontal resolution, which has been an operational numerical weather prediction model at the Korea Meteorological Administration since being adopted from the Met Office in 2011. Relative to the ERA-I, in terms of skill scores, the EARR performance for wind, temperature, relative humidity, and geopotential height improves except for mean sea level pressure, the lower-troposphere geopotential height, and the upper-air relative humidity. In a similar way, RMSEs of the EARR are smaller than those of ERA-I for wind, temperature, and relative humidity, except for the upper-air meridional wind and the upper-air relative humidity in January. With respect to the near-surface variables, the triple collocation analysis and the correlation coefficients confirm that EARR provides a much improved representation when compared with ERA-I. In addition, EARR reproduces the finescale features of near-surface variables in greater detail than ERA-I does, and the kinetic energy (KE) spectra of EARR agree more with the canonical atmospheric KE spectra than do the ERA-I KE spectra. On the basis of the fractions skill score, the near-surface wind of EARR is statistically significantly better simulated than that of ERA-I for all thresholds, except for the higher threshold at smaller spatial scales. Therefore, although special care needs to be taken when using the upper-air relative humidity from EARR, the near-surface variables of the EARR that were developed are found to be more accurate than those of ERA-I.

scholarly journals Fennec dust forecast intercomparison over the Sahara in June 2011

2016 ◽  
Vol 16 (11) ◽  
pp. 6977-6995 ◽  
Author(s):  
Jean-Pierre Chaboureau ◽  
Cyrille Flamant ◽  
Thibaut Dauhut ◽  
Cécile Kocha ◽  
Jean-Philippe Lafore ◽  
...  
Keyword(s):  
High Resolution ◽  
Surface Wind ◽  
Dust Emission ◽  
Airborne Lidar ◽  
Data Sets ◽  
Density Currents ◽  
Data Set ◽  
Near Surface ◽  
Western Sahara ◽  
Deep Well

Abstract. In the framework of the Fennec international programme, a field campaign was conducted in June 2011 over the western Sahara. It led to the first observational data set ever obtained that documents the dynamics, thermodynamics and composition of the Saharan atmospheric boundary layer (SABL) under the influence of the heat low. In support to the aircraft operation, four dust forecasts were run daily at low and high resolutions with convection-parameterizing and convection-permitting models, respectively. The unique airborne and ground-based data sets allowed the first ever intercomparison of dust forecasts over the western Sahara. At monthly scale, large aerosol optical depths (AODs) were forecast over the Sahara, a feature observed by satellite retrievals but with different magnitudes. The AOD intensity was correctly predicted by the high-resolution models, while it was underestimated by the low-resolution models. This was partly because of the generation of strong near-surface wind associated with thunderstorm-related density currents that could only be reproduced by models representing convection explicitly. Such models yield emissions mainly in the afternoon that dominate the total emission over the western fringes of the Adrar des Iforas and the Aïr Mountains in the high-resolution forecasts. Over the western Sahara, where the harmattan contributes up to 80 % of dust emission, all the models were successful in forecasting the deep well-mixed SABL. Some of them, however, missed the large near-surface dust concentration generated by density currents and low-level winds. This feature, observed repeatedly by the airborne lidar, was partly forecast by one high-resolution model only.

scholarly journals Interpolation framework to speed up near-surface wind simulations for data-driven wildfire applications

2018 ◽  
Vol 27 (4) ◽  
pp. 257 ◽  
Author(s):  
O. Rios ◽  
W. Jahn ◽  
E. Pastor ◽  
M. M. Valero ◽  
E. Planas
Keyword(s):  
High Resolution ◽  
Surface Wind ◽  
Computation Time ◽  
Data Driven ◽  
Wind Fields ◽  
Near Surface ◽  
Finite Set ◽  
Multiple Resolutions ◽  
Feasible Alternative ◽  
Wildfire Spread

Local wind fields that account for topographic interaction are a key element for any wildfire spread simulator. Currently available tools to generate near-surface winds with acceptable accuracy do not meet the tight time constraints required for data-driven applications. This article presents the specific problem of data-driven wildfire spread simulation (with a strategy based on using observed data to improve results), for which wind diagnostic models must be run iteratively during an optimisation loop. An interpolation framework is proposed as a feasible alternative to keep a positive lead time while minimising the loss of accuracy. The proposed methodology was compared with the WindNinja solver in eight different topographic scenarios with multiple resolutions and reference – pre-run– wind map sets. Results showed a major reduction in computation time (~100 times once the reference fields are available) with average deviations of 3% in wind speed and 3° in direction. This indicates that high-resolution wind fields can be interpolated from a finite set of base maps previously computed. Finally, wildfire spread simulations using original and interpolated maps were compared showing minimal deviations in the fire shape evolution. This methodology may have an important effect on data assimilation frameworks and probabilistic risk assessment where high-resolution wind fields must be computed for multiple weather scenarios.

scholarly journals High-resolution numerical modeling of mesoscale island wakes and sensitivity to static topographic relief data

2015 ◽  
Vol 8 (8) ◽  
pp. 2645-2653 ◽  
Author(s):  
C. G. Nunalee ◽  
Á. Horváth ◽  
S. Basu
Keyword(s):  
High Resolution ◽  
Vortex Shedding ◽  
Weather Prediction ◽  
Surface Wind ◽  
Wrf Model ◽  
Data Sets ◽  
Data Set ◽  
Near Surface ◽  
Nwp Model ◽  
Height Data

Abstract. Recent decades have witnessed a drastic increase in the fidelity of numerical weather prediction (NWP) modeling. Currently, both research-grade and operational NWP models regularly perform simulations with horizontal grid spacings as fine as 1 km. This migration towards higher resolution potentially improves NWP model solutions by increasing the resolvability of mesoscale processes and reducing dependency on empirical physics parameterizations. However, at the same time, the accuracy of high-resolution simulations, particularly in the atmospheric boundary layer (ABL), is also sensitive to orographic forcing which can have significant variability on the same spatial scale as, or smaller than, NWP model grids. Despite this sensitivity, many high-resolution atmospheric simulations do not consider uncertainty with respect to selection of static terrain height data set. In this paper, we use the Weather Research and Forecasting (WRF) model to simulate realistic cases of lower tropospheric flow over and downstream of mountainous islands using the default global 30 s United States Geographic Survey terrain height data set (GTOPO30), the Shuttle Radar Topography Mission (SRTM), and the Global Multi-resolution Terrain Elevation Data set (GMTED2010) terrain height data sets. While the differences between the SRTM-based and GMTED2010-based simulations are extremely small, the GTOPO30-based simulations differ significantly. Our results demonstrate cases where the differences between the source terrain data sets are significant enough to produce entirely different orographic wake mechanics, such as vortex shedding vs. no vortex shedding. These results are also compared to MODIS visible satellite imagery and ASCAT near-surface wind retrievals. Collectively, these results highlight the importance of utilizing accurate static orographic boundary conditions when running high-resolution mesoscale models.

Climatology of near-surface wind patterns over Switzerland

2001 ◽  
Vol 21 (7) ◽  
pp. 809-827 ◽  
Author(s):  
Rudolf O. Weber ◽  
Markus Furger
Keyword(s):  
Surface Wind ◽  
Near Surface ◽  
Wind Patterns

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 An experimental 2DVAR retrieval using AMSR2

2019 ◽  
Author(s):  
David Ian Duncan ◽  
Patrick Eriksson ◽  
Simon Pfreundschuh
Keyword(s):  
Wind Speed ◽  
Spatial Resolution ◽  
Spatial Scales ◽  
Surface Wind ◽  
Optimal Estimation ◽  
Surface Wind Speed ◽  
Model Errors ◽  
Near Surface ◽  
Noise Characteristics ◽  
Microwave Imager

Abstract. A two-dimensional variational retrieval (2DVAR) is presented for a passive microwave imager. The overlapping antenna patterns of all frequencies from the Advanced Microwave Scanning Radiometer-2 (AMSR2) are explicitly simulated to attempt retrieval of near surface wind speed and surface skin temperature at finer spatial scales than individual antenna beams. This is achieved, with the effective spatial resolution of retrieved parameters shown by analysis of 2DVAR averaging kernels. Sea surface temperature retrievals achieve about 30 km resolution, with wind speed retrievals at about 10 km resolution. It is argued that multi-dimensional optimal estimation permits greater use of total information content from microwave sensors than other methods, with no compromises on target resolution needed; instead, various targets are retrieved at the highest possible spatial resolution, driven by the channels' sensitivities. All AMSR2 channels can be simulated within near their published noise characteristics for observed clear-sky scenes, though calibration and emissivity model errors are key challenges. This experimental retrieval shows the feasibility of 2DVAR for cloud-free retrievals, and opens the possibility of standalone 3DVAR retrievals of water vapour and hydrometeor fields from microwave imagers in the future. The results have implications for future satellite missions and sensor design, as spatial oversampling can somewhat mitigate the need for larger antennas in the push for higher spatial resolution.

scholarly journals An Assessment of NASA’s GMAO MERRA-2 Reanalysis Surface Winds

2019 ◽  
Vol 32 (23) ◽  
pp. 8261-8281 ◽  
Author(s):  
D. Carvalho
Keyword(s):  
Surface Wind ◽  
The Other ◽  
Surface Winds ◽  
Wind Fields ◽  
Near Surface ◽  
Wind Speeds ◽  
Wide Range ◽  
Ocean Surface Winds ◽  
The Tropics ◽  
Global Surface

Abstract The quality of MERRA-2 surface wind fields was assessed by comparing them with 10 years of measurements from a wide range of surface wind observing platforms. This assessment includes a comparison of MERRA-2 global surface wind fields with the ones from its predecessor, MERRA, to assess if GMAO’s latest reanalyses improved the representation of the global surface winds. At the same time, surface wind fields from other modern reanalyses—NCEP-CFSR, ERA-Interim, and JRA-55—were also included in the comparisons to evaluate MERRA-2 global surface wind fields in the context of its contemporary reanalyses. Results show that MERRA-2, CFSR, ERA-Interim, and JRA-55 show similar error metrics while MERRA consistently shows the highest errors. Thus, when compared with wind observations, the accuracy of MERRA-2 surface wind fields represents a clear improvement over its predecessor MERRA and is in line with the other contemporary reanalyses in terms of the representation of global near-surface wind fields. All reanalyses showed a tendency to underestimate ocean surface winds (particularly in the tropics) and, oppositely, to overestimate inland surface winds (except JRA-55, which showed a global tendency to underestimate the wind speeds); to represent the wind direction rotated clockwise in the Northern Hemisphere (positive bias) and anticlockwise in the Southern Hemisphere (negative bias), with the exception of JRA-55; and to show higher errors near the poles and in the ITCZ, particularly in the equatorial western coasts of Central America and Africa. However, MERRA-2 showed substantially lower wind errors in the poles when compared with the other reanalyses.

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