scholarly journals Sensitivity study of surface wind flow of a limited area model simulating the extratropical storm Delta affecting the Canary Islands

2009 ◽  
Vol 2 (1) ◽  
pp. 151-157 ◽  
Author(s):  
C. Marrero ◽  
O. Jorba ◽  
E. Cuevas ◽  
J. M. Baldasano

Abstract. In November 2005 an extratropical storm named Delta affected the Canary Islands (Spain). The high sustained wind and intense gusts experienced caused significant damage. A numerical sensitivity study of Delta was conducted using the Weather Research & Forecasting Model (WRF-ARW). A total of 27 simulations were performed. Non-hydrostatic and hydrostatic experiments were designed taking into account physical parameterizations and geometrical factors (size and position of the outer domain, definition or not of nested grids, horizontal resolution and number of vertical levels). The Factor Separation Method was applied in order to identify the major model sensitivity parameters under this unusual meteorological situation. Results associated to percentage changes relatives to a control run simulation demonstrated that boundary layer and surface layer schemes, horizontal resolutions, hydrostaticity option and nesting grid activation were the model configuration parameters with the greatest impact on the 48 h maximum 10 m horizontal wind speed solution.

2017 ◽  
Vol 34 (6) ◽  
pp. 1371-1386 ◽  
Author(s):  
Benjamin Witschas ◽  
Stephan Rahm ◽  
Andreas Dörnbrack ◽  
Johannes Wagner ◽  
Markus Rapp

AbstractAirborne coherent Doppler wind lidar measurements, acquired during the Gravity Wave Life-Cycle (GW-LCYCLE) I field campaign performed from 2 to 14 December 2013 in Kiruna, Sweden, are used to investigate internal gravity waves (GWs) induced by flow across the Scandinavian Mountains. Vertical wind speed is derived from lidar measurements with a mean bias of less than 0.05 m s−1 and a standard deviation of 0.2 m s−1 by correcting horizontal wind projections onto the line-of-sight direction by means of ECMWF wind data. The horizontal wind speed and direction are retrieved from lidar measurements by applying a velocity–azimuth display scan and a spectral accumulation technique, leading to a horizontal resolution of about 9 km along the flight track and a vertical resolution of 100 m, respectively. Both vertical and horizontal wind measurements are valuable for characterizing GW properties as demonstrated by means of a flight performed on 13 December 2013 acquired during weather conditions favorable for orographic GW excitation. Wavelet power spectra of the vertical wind speed indicate that the horizontal GW wavelengths lay mainly between 10 and 30 km and that the GW amplitude above the mountain ridge decreases with increasing altitude. Additionally, the perturbations of the horizontal wind speed are analyzed, showing horizontal wavelengths in the excitation region of 100–125 km with upwind-tilted wave fronts. By means of elevation power spectra, it is revealed that vertical wind power spectra are dominated by the short-wave elevation part, whereas horizontal wind perturbations are dominated by the long-wave part.


When Monsoon depressions form over the seas, the Moderate Resolution Imaging Spectroradiometer (MODIS) provides humidity and high-horizontal resolution temperature details about the depressions. These high-resolution satellite data related to temperature and humidity can improve the poor predicting rate of depressions [1]. Using three-dimensional variational data assimilation (3DVAR) and with the help of humidity profiles along with MODIS temperature. We can achieve an advanced prospect of detection and a larger value of (ETS) equitable threat score observed over 48 hours collected precipitation with respect to the control run. The 3DVAR assimilation of Doppler Weather Radar wind data associated with Indian Meteorological Department (IMD) surface data and upper air data helped in the improvements in the simulation of strong gradients associated with horizontal wind speed ,higher warm core temperature , high vertical velocity & better precipitation and spatial distribution.[2]. The effect of Spectral sensor microwave imager (SSM/I), humidity profiles, use of Advanced TIROS Vertical Sounder (ATOVS) temperature and total precipitable water (TPW) helped in improving the ‘‘forecast impact’’ parameters of ‘‘bias score’’ and ‘‘equitable threat score’’ with respect to the assimilation of satellite observation[3] . In this paper we have discussed a comparative study of different proposed techniques to analyze its effects in improving the low prediction rates of depressions.


Author(s):  
Claudia Christine Stephan

AbstractSatellite images frequently show mesoscale arc-shaped cloud lines with a spacing of several tens of kilometers. These clouds form in a shallow mixed boundary layer in locations where the near-surface horizontal wind speed exceeds ~7 ms−1. Unlike other mesoscale cloud line phenomena, such as horizontal convective rolls, these cloud lines do not align with the wind direction but form at large oblique angles to the near-surface wind. A particularly distinct event of this pattern developed on Jan 31, 2020 over the western tropical Atlantic. Radiosonde soundings are available for this time and location, allowing a detailed analysis. By comparing observations to theoretical predictions based on Jeffreys’ drag-instability mechanism, it is shown that draginstability waves may contribute to the formation of this cloud pattern. The theory is formulated in only two dimensions and predicts that wave-like horizontal wind perturbations of this wavelength can grow, because they modulate the surface friction in a way that reinforces the perturbations. The theoretical horizontal wavelengths of 40–80 km agree with the observations. Streamlines from the ERA5 reanalysis show that the directional change of the near-surface wind is likely to contribute to the arc-shape, but that a radial propagation of an initial instability is also required to explain the strong curvature. Moreover, ERA5 winds suggest that other known explanations for the formation of cloud lines are unlikely to apply in the case studied here.


2021 ◽  
Vol 13 (11) ◽  
pp. 2103
Author(s):  
Yuchen Liu ◽  
Jia Liu ◽  
Chuanzhe Li ◽  
Fuliang Yu ◽  
Wei Wang

An attempt was made to evaluate the impact of assimilating Doppler Weather Radar (DWR) reflectivity together with Global Telecommunication System (GTS) data in the three-dimensional variational data assimilation (3DVAR) system of the Weather Research Forecast (WRF) model on rain storm prediction in Daqinghe basin of northern China. The aim of this study was to explore the potential effects of data assimilation frequency and to evaluate the outputs from different domain resolutions in improving the meso-scale NWP rainfall products. In this study, four numerical experiments (no assimilation, 1 and 6 h assimilation time interval with DWR and GTS at 1 km horizontal resolution, 6 h assimilation time interval with radar reflectivity, and GTS data at 3 km horizontal resolution) are carried out to evaluate the impact of data assimilation on prediction of convective rain storms. The results show that the assimilation of radar reflectivity and GTS data collectively enhanced the performance of the WRF-3DVAR system over the Beijing-Tianjin-Hebei region of northern China. It is indicated by the experimental results that the rapid update assimilation has a positive impact on the prediction of the location, tendency, and development of rain storms associated with the study area. In order to explore the influence of data assimilation in the outer domain on the output of the inner domain, the rainfall outputs of 3 and 1 km resolution are compared. The results show that the data assimilation in the outer domain has a positive effect on the output of the inner domain. Since the 3DVAR system is able to analyze certain small-scale and convective-scale features through the incorporation of radar observations, hourly assimilation time interval does not always significantly improve precipitation forecasts because of the inaccurate radar reflectivity observations. Therefore, before data assimilation, the validity of assimilation data should be judged as far as possible in advance, which can not only improve the prediction accuracy, but also improve the assimilation efficiency.


2013 ◽  
Vol 17 (6) ◽  
pp. 2107-2120 ◽  
Author(s):  
S. Davolio ◽  
M. M. Miglietta ◽  
T. Diomede ◽  
C. Marsigli ◽  
A. Montani

Abstract. Numerical weather prediction models can be coupled with hydrological models to generate streamflow forecasts. Several ensemble approaches have been recently developed in order to take into account the different sources of errors and provide probabilistic forecasts feeding a flood forecasting system. Within this framework, the present study aims at comparing two high-resolution limited-area meteorological ensembles, covering short and medium range, obtained via different methodologies, but implemented with similar number of members, horizontal resolution (about 7 km), and driving global ensemble prediction system. The former is a multi-model ensemble, based on three mesoscale models (BOLAM, COSMO, and WRF), while the latter, following a single-model approach, is the operational ensemble forecasting system developed within the COSMO consortium, COSMO-LEPS (limited-area ensemble prediction system). The meteorological models are coupled with a distributed rainfall-runoff model (TOPKAPI) to simulate the discharge of the Reno River (northern Italy), for a recent severe weather episode affecting northern Apennines. The evaluation of the ensemble systems is performed both from a meteorological perspective over northern Italy and in terms of discharge prediction over the Reno River basin during two periods of heavy precipitation between 29 November and 2 December 2008. For each period, ensemble performance has been compared at two different forecast ranges. It is found that, for the intercomparison undertaken in this specific study, both mesoscale model ensembles outperform the global ensemble for application at basin scale. Horizontal resolution is found to play a relevant role in modulating the precipitation distribution. Moreover, the multi-model ensemble provides a better indication concerning the occurrence, intensity and timing of the two observed discharge peaks, with respect to COSMO-LEPS. This seems to be ascribable to the different behaviour of the involved meteorological models. Finally, a different behaviour comes out at different forecast ranges. For short ranges, the impact of boundary conditions is weaker and the spread can be mainly attributed to the different characteristics of the models. At longer forecast ranges, the similar behaviour of the multi-model members forced by the same large-scale conditions indicates that the systems are governed mainly by the boundary conditions, although the different limited area models' characteristics may still have a non-negligible impact.


2011 ◽  
Vol 12 (1) ◽  
pp. 27-44 ◽  
Author(s):  
Michael Kunz

Abstract Simulations of orographic precipitation over the low mountain ranges of southwestern Germany and eastern France with two different physics-based linear precipitation models are presented. Both models are based on 3D airflow dynamics from linear theory and consider advection of condensed water and leeside drying. Sensitivity studies for idealized conditions and a real case study show that the amount and spatial distribution of orographic precipitation is strongly controlled by characteristic time scales for cloud and hydrometeor advection and background precipitation due to large-scale lifting. These parameters are estimated by adjusting the model results on a 2.5-km grid to observed precipitation patterns for a sample of 40 representative orography-dominated stratiform events (24 h) during a calibration period (1971–80). In general, the best results in terms of lowest rmse and bias are obtained for characteristic time scales of 1600 s and background precipitation of 0.4 mm h−1. Model simulations of a sample of 84 events during an application period (1981–2000) with fixed parameters demonstrate that both models are able to reproduce quantitatively precipitation patterns obtained from observations and reanalyses from a numerical model [Consortium for Small-scale Modeling (COSMO)]. Combining model results with observation data shows that heavy precipitations over mountains are restricted to situations with strong atmospheric forcings in terms of synoptic-scale lifting, horizontal wind speed, and moisture content.


2021 ◽  
Author(s):  
Steven Knoop ◽  
Fred Bosveld ◽  
Marijn de Haij ◽  
Arnoud Apituley

<p>Atmospheric motion and turbulence are essential parameters for weather and topics related to air quality. Therefore, wind profile measurements play an important role in atmospheric research and meteorology. One source of wind profile data are Doppler wind lidars, which are laser-based remote sensing instruments that measure wind speed and wind direction up to a few hundred meters or even a few kilometers. Commercial wind lidars use the laser wavelength of 1.5 µm and therefore backscatter is mainly from aerosols while clear air backscatter is minimal, limiting the range to the boundary layer typically.</p><p>We have carried out a two-year intercomparison of the ZephIR 300M (ZX Lidars) short-range wind lidar and tall mast wind measurements at Cabauw [1]. We have focused on the (height-dependent) data availability of the wind lidar under various meteorological conditions and the data quality through a comparison with in situ wind measurements at several levels in the 213m tall meteorological mast. We have found an overall availability of quality-controlled wind lidar data of 97% to 98 %, where the missing part is mainly due to precipitation events exceeding 1 mm/h or fog or low clouds below 100 m. The mean bias in the horizontal wind speed is within 0.1 m/s with a high correlation between the mast and wind lidar measurements, although under some specific conditions (very high wind speed, fog or low clouds) larger deviations are observed. This instrument is being deployed within North Sea wind farms.</p><p>Recently, a scanning long-range wind lidar Windcube 200S (Leosphere/Vaisala) has been installed at Cabauw, as part of the Ruisdael Observatory program [2]. The scanning Doppler wind lidars will provide detailed measurements of the wind field, aerosols and clouds around the Cabauw site, in coordination with other instruments, such as the cloud radar.</p><p>[1] Knoop, S., Bosveld, F. C., de Haij, M. J., and Apituley, A.: A 2-year intercomparison of continuous-wave focusing wind lidar and tall mast wind measurements at Cabauw, Atmos. Meas. Tech., 14, 2219–2235, 2021</p><p>[2] https://ruisdael-observatory.nl/</p>


2012 ◽  
Vol 8 (1) ◽  
pp. 83-86 ◽  
Author(s):  
J. G. Pedersen ◽  
M. Kelly ◽  
S.-E. Gryning ◽  
R. Floors ◽  
E. Batchvarova ◽  
...  

Abstract. Vertical profiles of the horizontal wind speed and of the standard deviation of vertical wind speed from Large Eddy Simulations of a convective atmospheric boundary layer are compared to wind LIDAR measurements up to 1400 m. Fair agreement regarding both types of profiles is observed only when the simulated flow is driven by a both time- and height-dependent geostrophic wind and a time-dependent surface heat flux. This underlines the importance of mesoscale effects when the flow above the atmospheric surface layer is simulated with a computational fluid dynamics model.


2020 ◽  
Vol 21 (12) ◽  
pp. 2829-2853 ◽  
Author(s):  
Marouane Temimi ◽  
Ricardo Fonseca ◽  
Narendra Nelli ◽  
Michael Weston ◽  
Mohan Thota ◽  
...  

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.


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