Sensitivity analysis of WRF model PBL schemes in simulating boundary-layer variables in southern Italy: An experimental campaign

Avolio, Elenio; Federico, Stefano; Miglietta, Mario Marcello; Feudo, Teresa Lo; Calidonna, Claudia Roberta; Sempreviva, Anna Maria

doi:10.1016/j.atmosres.2017.04.003

Cited by 87 publications

(49 citation statements)

References 42 publications

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“…The general overestimation of the WRF modelled wind speed found in the current study is in agreement with other studies performed using this mesoscalar model over different regions (see e. g. Borge et al, 2008;Draxl et al, 2014;Hariprasad et al, 2014;Santos-Alamillos et al, 2015;Kalverla et al, 2016;Avolio et al, 2017). A plausible reason for this wind speed overestimation could be a lack of frictional drag near the surface (Kalverla et al, 2016).…”

Section: Resultssupporting

confidence: 91%

“…Hu et al, 2010;Zhang et al, 2013), and also in Europe (see e.g. Avolio et al, 2017) or tropical areas (Xie et al, 2012). Although just highlighting here the differences in the temperature field trends, the contrast of both models is also found in other sensible surface weather parameters, such as the surface heat fluxes or the moisture field (Tolk et al, 2009;Steeneveld et al, 2011), as well as considering the wind field or the downwelling shortwave radiation (Avolio et al, 2016).…”

Section: Introductionmentioning

confidence: 65%

“…Hu et al, 2010;Steeneveld et al, 2011). A more recent study performed by Avolio et al (2017) over the Mediterranean area in Calabria Region (Southern Italy) points that this model issue could be related to an overestimation of the surface wind that transport moist and cold air from the sea under breeze circulations. They consider that an overestimation of this flow from the sea could produce this temperature cold bias.…”

Section: Resultsmentioning

confidence: 99%

“…Therefore, a lot of efforts have been dedicated in the last years with the aim of evaluating and improving the forecast results of both models. For instance, different studies have been performed considering the formulation of the Planetary Boundary Layer (see e. g. Borge et al, 2008;Hu et al, 2010;Steeneveld et al, 2011;Draxl et al, 2014;Hariprasad et al, 2014;Gómez et al, 2016b;Avolio et al, 2017) or the land surface and atmosphere interactions (see e. g. Hong et al, 2009;Tolk et al, 2009;Dillon et al, 2016;Kioutsioukis et al, 2016;Lara-Fanego et al, 2016;Santanello et al, 2016;Gómez et al, 2018), among others. On the other hand, the largest discrepancies between model results and observations are typically observed for cumulus precipitation (amount, location, duration, type, etc.)…”

Section: Introductionmentioning

confidence: 99%

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Comparative assessment of RAMS and WRF short-term forecasts over Eastern Iberian Peninsula using various in-situ observations, remote sensing products and uncoupled land surface model datasets

Gómez

Caselles

Estrela

et al. 2018

Atmospheric Research

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The Regional Atmospheric Modeling System (RAMS) and the Weather Research and Forecasting (WRF) mesoscale models are being used for weather and air quality studies as well as forecasting tools in Numerical Weather Prediction (NWP) systems. In the current study, we perform a comparative assessment of these models under distinct typical atmospheric conditions, classified according to the dominant wind flow and cloudiness, over Eastern Iberian Peninsula. This study is focused on the model representation of key physical processes in terms of meteorology and surface variables during a 7-days period in summer 2011. The hourly outputs produced by these two models are compared not only with observed standard surface variables, measured at different permanent weather stations located over the region of study, but also with different surface remote sensing products and uncoupled Land Surface Models (LSM) datasets. Confronting RAMS and WRF, the current study highlights relevant differences over areas near the coast when mesoscale circulations or Eastern synoptic advections are developed over the region of study. A higher moisture content is observed under these atmospheric conditions, due to the moisture transport by the sea breeze inland. In this regard, it has been found that the Eastern wind field simulated by WRF reaches inland areas and comprises a larger sea breeze extension than RAMS. This sea breeze development impacts meteorology and surface variables in locations not too close to the coast, but still affected by land-sea winds. Additionally, WRF remains more windy and moister than RAMS at night-time, while alike results are found under Western synoptic advections. The results obtained in the current paper show differences under distinct dominant atmospheric conditions, which outline further research in this field in order to achieve more general conclusions.

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Section: Resultssupporting

confidence: 91%

Section: Introductionmentioning

confidence: 65%

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Comparative assessment of RAMS and WRF short-term forecasts over Eastern Iberian Peninsula using various in-situ observations, remote sensing products and uncoupled land surface model datasets

Gómez

Caselles

Estrela

et al. 2018

Atmospheric Research

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“…By contrast, the weather conditions for the P2 period showed typically clear weather that continued for a week, which were suitable for an improved simulation performance of the WRF model. In previous studies verifying WRF simulations performed in China, Spain, and India, the correlation coefficients for air temperature and wind speed ranged between 0.78–0.94 and 0.20–0.53, respectively [ 47 , 48 , 49 , 50 ]. Their similar values to the results of this study demonstrate that the meteorological inputs provided from the WRF model to the CFD model are appropriate.…”

Section: Resultsmentioning

confidence: 95%

Assessing 3-D Spatial Extent of Near-Road Air Pollution around a Signalized Intersection Using Drone Monitoring and WRF-CFD Modeling

Lee

Kwak

2020

IJERPH

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In this study, we have assessed the three-dimensional (3-D) spatial extent of near-road air pollution around a signalized intersection in a densely populated area using collaborating methodologies of stationary measurements, drone monitoring, and atmospheric dispersion modeling. Stationary measurement data collected in the roadside apartment building showed a substantial effect of emitted pollutants, such as nitrogen oxides (NOx), black carbon (BC), and ultrafine particles (UFPs), especially during the morning rush hours. Vertical drone monitoring near the road intersection exhibited a steeper decreasing trend with increasing altitude for BC concentration rather than for fine particulate matter (PM2.5) concentration below the apartment building height. Atmospheric NOx dispersion was simulated using the weather research and forecasting (WRF) and computational fluid dynamics (CFD) models for the drone measurement periods. Based on the agreement between the measured BC and simulated NOx concentrations, we concluded that the air pollution around the road intersection has adverse effects on the health of residents living within the 3-D spatial extent within at least 120 m horizontally and a half of building height vertically during the morning rush hours. The comparability between drone monitoring and WRF-CFD modeling can further guarantee the identification of air pollution hotspots using the methods.

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Observed aerosol‐layer depth at Station Nord in the high Arctic

Gryning

Batchvarova

Floors

et al. 2023

Intl Journal of Climatology

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The depth of the aerosol layer at the Villum Research Station at Station Nord in the high Arctic is analysed based on 8 years of observations from a ceilometer and one full year from a wind lidar. The layer is of particular interest for aerosol process modelling and atmospheric chemistry studies. The depth of the aerosol layer is assigned to the inflection point in the attenuated backscatter profile by two methods; one is based on polynomial approximation of the profile and the other is direct numerical differentiation. The analysis is based on two types of hourly profiles; one consists of averaging the attenuated backscatter observations and the other by computing the median. Due to sporadic occurrence of outliers in the ranges around 50 m in the ceilometer observations, this part of the profile is not used in this study. Restricting the observations to heights above 100 m, the depths of the aerosol layer are found to be typically ≈230 m. It varies little between winter and summer, but the spread in the depth is larger during the winter as compared to summer. To extend the study of the aerosol-layer depth below 100 m, a method is applied that combines the ceilometer measurements with the carrier-to-noise ratio from the wind lidar. The results are available for 2018 only, and they show aerosol-layer depths below ≈80 m as well as depths around 230 m and they show few observations between ≈80 and ≈230 m. Near the ground, the observed backscatter exhibits a pronounced seasonal variation, having low values during the summer and high values during the winter. The strength of the seasonal variability decreases with height, especially above the aerosol-layer depth, and is virtually absent at 1 km. K E Y W O R D Saerosol-layer depth, attenuated backscatter profiles, carrier-to-noise ratio, ceilometer, high Arctic, wind lidar

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Sensitivity analysis of WRF model PBL schemes in simulating boundary-layer variables in southern Italy: An experimental campaign

Cited by 87 publications

References 42 publications

Comparative assessment of RAMS and WRF short-term forecasts over Eastern Iberian Peninsula using various in-situ observations, remote sensing products and uncoupled land surface model datasets

Comparative assessment of RAMS and WRF short-term forecasts over Eastern Iberian Peninsula using various in-situ observations, remote sensing products and uncoupled land surface model datasets

Assessing 3-D Spatial Extent of Near-Road Air Pollution around a Signalized Intersection Using Drone Monitoring and WRF-CFD Modeling

Observed aerosol‐layer depth at Station Nord in the high Arctic

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