Potentialities of the Numerical Weather Prediction model WRF to produce attenuation statistics in tropical regions

Mire, Valentin Le; Boulanger, Xavier; Castanet, Laurent; Benammar, Bouchra; Féral, Laurent

doi:10.23919/eucap48036.2020.9135414

Cited by 6 publications

(15 citation statements)

References 4 publications

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“…Such investigations on this NWP model have been conducted for feasibility of model to predict rain attenuation statistical properties . 6,7 In order to realize the dust storm and intense aerosol event occurred on 12 September 2020 in Polatli region accurately, we conducted several simulations on Weather Research and Forecasting (WRF) model with dedicated aerosol‐aware microphysics schemes. A Thompson microphysics scheme parametrization is carried out in order to determine the aerosol effects on rainfall and satellite TT&C signals.…”

Section: Methodsmentioning

confidence: 99%

Preliminary results on estimation of signal fading on telecommunication satellite telemetry signals with hybrid numerical weather prediction and artificial neural network approach under presence of aerosol effect

Gozutok

Yilmaz

Demirel

2022

Satell Commun Network

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In this research, an implementation of artificial deep neural networks (ANN) over outputs of 24-h multi-domain high-resolution nested real case Weather Research and Forecasting (WRF) model runs was carried out over two high-resolution simulation domains, which are tested and compared for rainfall generation in order to assess the signal fading event observed on geostationary telecommunication spacecraft in orbit for a real multiscale storm case. Our methodology of ANN, which is driven by WRF model output parameters, focuses on prediction of the rain attenuation signal impairment which is observed on the communication satellite telemetry (TM) downlink signal levels under significant aerosol presence due to dust storm which occurred on 12 September 2020. This modelling approach is then compared to rain attenuation observed on TM signal and correlated with communication satellite ground station TM signal measurements. Preliminary results from conducted error analysis (RMSE) on multiple input single output feed-forward neural network (MISO FFNN) prediction model outputs tested with several neural algorithms indicate good correlation with the TM downlink signal attenuation observations taken from the ground station TM baseband demodulator.

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Section: Methodsmentioning

confidence: 99%

Preliminary results on estimation of signal fading on telecommunication satellite telemetry signals with hybrid numerical weather prediction and artificial neural network approach under presence of aerosol effect

Gozutok

Yilmaz

Demirel

2022

Satell Commun Network

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“…eir main geographical [39] (latitude, longitude, and altitude) and geometrical (elevation angle) characteristics are presented in Table 2.…”

Section: The Reference Databasementioning

confidence: 99%

Preliminary Investigation of the Potentialities of a Mesoscale Meteorological Model to Reproduce Experimental Statistics of Rain Attenuation on Earth-Space Links

Castanet

Mire

Queyrel

et al. 2022

International Journal of Antennas and Propagation

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Current spatial resolutions achieved by mesoscale weather forecast models allow them to be used to generate the state of the lowest layers of the atmosphere over areas as small as a few square kilometers which corresponds to the typical size of the tropospheric area crossed by Earth-space links. Furthermore, they allow the evolution of the troposphere to be predicted with a time stamp of five minutes instead of every hour with large-scale weather forecast models which makes them attractive for radio propagation predictions for satellite communication applications. This paper aims at studying the capability of the Weather Research and Forecast (WRF) model coupled with an electromagnetic physical model to reproduce rain attenuation statistics for Earth-space paths at Ka-band. To this purpose, one year of propagation measurements collected at 20 GHz in different places at midlatitudes in Toulouse and Salon de Provence (France), Spino d’Adda (Italy), Aveiro (Portugal), and Madrid (Spain), at high latitudes in Svalbard (Norway) and at low latitudes in Kourou are used to make comparisons between simulations and measurements. Comparisons between the simulated and the experimental annual statistics considered in this paper provide encouraging results, with a similar accuracy as Recommendation ITU-R P.618–13 for midlatitude European locations and with better accuracy for a high latitude area in Svalbard and for an equatorial location in French Guiana.

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“…The common parameters of the WRF simulations are inspired by previous results with the models [5], [16]:…”

Section: B Nwp Configurationsmentioning

confidence: 99%

“…A more thorough statistical validation of the NWP performances would however still benefit any design based on them. In particular, the selection of NWP parametrizations should be assessed to correspond to the climatic specificities, not only in temperate regions, but also for equatorial and tropical regions where fewer measurements exist [16], to capture seasonal/monthly variations.…”

Section: Introductionmentioning

confidence: 99%

Rain Attenuation Estimation with the Numerical Weather Prediction Model WRF: Impact of Rain Drop Size Distribution for a Temperate Climate

Quibus

Mire

Queyrel

et al. 2021

2021 15th European Conference on Antennas and Propagation (EuCAP)

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Frequencies at and above K/Ka band are required for the deployment of (very) high throughput satellites. Yet, radio-links at those frequencies are strongly affected by tropospheric constituents, especially rain. The knowledge of the signal attenuation due to rain comes from dedicated propagation experiments with satellite beacons. Numerical Weather Prediction models could act as an alternative source of rain information, but the validation of their performances against beacon data remains incomplete, notably with respect to the local climatology. This work takes a look at the rain attenuation predicted with the Weather Research and Forecasting (WRF) model 4.0.3 initialized with ERA-5 data, tests nine microphysics schemes, either single-or double-moment, and adapts rigorously the electromagnetic model to their assumed rain drop size distributions. Results are compared over three months in Toulouse, in a temperate region, at both 20.2 and 39.4 GHz, and a strategy is outlined to select the best parametrizations from the error metrics.

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Potentialities of the Numerical Weather Prediction model WRF to produce attenuation statistics in tropical regions

Cited by 6 publications

References 4 publications

Preliminary results on estimation of signal fading on telecommunication satellite telemetry signals with hybrid numerical weather prediction and artificial neural network approach under presence of aerosol effect

Preliminary results on estimation of signal fading on telecommunication satellite telemetry signals with hybrid numerical weather prediction and artificial neural network approach under presence of aerosol effect

Preliminary Investigation of the Potentialities of a Mesoscale Meteorological Model to Reproduce Experimental Statistics of Rain Attenuation on Earth-Space Links

Rain Attenuation Estimation with the Numerical Weather Prediction Model WRF: Impact of Rain Drop Size Distribution for a Temperate Climate

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