Reanalysis profile downscaling with WRF model and sensitivity to PBL parameterization schemes over a subtropical station

Diaz, Lucas Ribeiro; Santos, Daniel Caetano; Käfer, Pâmela Suélen; Iglesias, María Luján; Rocha, Nájila Souza da; Costa, S. T. L.; Kaiser, Eduardo André; Rolim, Silvia Beatriz Alves

doi:10.1016/j.jastp.2021.105724

Cited by 6 publications

(3 citation statements)

References 82 publications

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“…In the analyzed period of 2001-2010, Pearson correlation coefficients reached 0.97 for the whole year and did not fall below 0.92 if seasonal PW was considered. These results are in agreement with those obtained by, e.g., González et al [84], Fedele et al [85], Pérez-Jordán et al [23], Varga and Breuer [82] and Diaz et al [86], where the authors reported close agreement of the whole column of PW values. In our work, a similar model configuration was used [23], which was tested in the earlier work of González et al [84].…”

Section: Discussionsupporting

confidence: 92%

Precipitable Water Content Climatology over Poland

2022

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In this work, the high-resolution spatial and temporal variability of precipitable water (PW) over Poland is presented. PW is one of the key parameters of the atmosphere taken into account in thermodynamic and radiation models. The daily PW values from years 2001–2010, calculated with the use of the WRF model, were compared with PW from soundings. The WRF modeled PW is in close agreement with measurements for the whole column of the troposphere and for individual levels: below 1.5 km, 1.5–3 km, 3–6 km and 6–10 km. The best agreement is observed in the lower part of the troposphere, especially for winter months. At the levels of 1.5 km to 10 km, the WRF model overestimates the PW values throughout the year, whereas up to 1.5 km PW is underestimated. The study shows an increasing trend of PW annual values between 1983 and 2010, but the trend is statistically insignificant. A significant positive trend with a high Sen’s slope is observed for the summer season up to 3 km in the troposphere, along with a significant negative tendency for spring. The trends in PW over Poland and Central Europe identified in this study contribute to the ongoing discussion on the observed climate changes.

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Section: Discussionsupporting

confidence: 92%

Precipitable Water Content Climatology over Poland

2022

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“…The choice of a given set of physical parameterizations can have a significant impact in wind simulation and wind energy estimation over a given area. Several studies have dealt with the evaluation of the sensitivity of the WRF model to make the choice of PBL parameterizations in wind simulations [36][37][38][39][40][41][42][43][44][45][46][47]. These studies revealed that the simulation of the wind field is sensitive to the physical parameterization's selection, and that the performance of these parameterizations vary significantly according to the studied geographical region, highlighting the need to carry out sensitivity studies to determine the optimal model configuration for the simulation of the wind regime in a specific area.…”

Section: Introductionmentioning

confidence: 99%

Optimization and Evaluation of the Weather Research and Forecasting (WRF) Model for Wind Energy Resource Assessment and Mapping in Iran

Saadatabadi,

Hamzeh,

Kaskaoutis

et al. 2024

Applied Sciences

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This study aims to optimize the Weather Research and Forecasting (WRF) model regarding the choice of the best planetary boundary layer (PBL) physical scheme and to evaluate the model’s performance for wind energy assessment and mapping over the Iranian territory. In this initiative, five PBL and surface layer parameterization schemes were tested, and their performance was evaluated via comparison with observational wind data. The study used two-way nesting domains with spatial resolutions of 15 km and 5 km to represent atmospheric circulation patterns affecting the study area. Additionally, a seventeen-year simulation (2004–2020) was conducted, producing wind datasets for the entire Iranian territory. The accuracy of the WRF model was assessed by comparing its results with observations from multiple sites and with the high-resolution Global Wind Atlas. Statistical parameters and wind power density were calculated from the simulated data and compared with observations to evaluate wind energy potential at specific sites. The model’s performance was sensitive to the horizontal resolution of the terrain data, with weaker simulations for wind speeds below 3 m/s and above 10 m/s. The results confirm that the WRF model provides reliable wind speed data for realistic wind energy assessment studies in Iran. The model-generated wind resource map identifies areas with high wind (wind speed > 5.6 m/s) potential that are currently without wind farms or Aeolic parks for exploitation of the wind energy potential. The Sistan Basin in eastern Iran was identified as the area with the highest wind power density, while areas west of the Zagros Mountains and in southwest Iran showed high aeolian potential during summer. A novelty of this research is the application of the WRF model in an area characterized by high topographical complexities and specific geographical features. The results provide practical solutions and valuable insights for industry stakeholders, facilitating informed decision making, reducing uncertainties, and promoting the effective utilization of wind energy resources in the region.

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“…Recent review studies have shown that although many studies on the evaluation and comparison of PBL parameterization schemes have been undertaken, there is still no uniform conclusion on which PBL parameterization scheme performs best(Wenxing Jia and Zhang, 2020). Moreover, most of the evaluation work on PBL parameterization schemes is done for individual cases or a particular region (Avolio et al, 2017;Diaz et al, 2021;Falasca et al, 2021;Ferrero et al, 2018;He et al, 2022;Shen et al, 2022). In spite of those, simulation results for the PBL parameterization schemes are more uniform: (1) the simulation of temperature is better than that of relative humidity, and the simulation of wind speed and direction is worse.…”

Section: Introductionmentioning

confidence: 99%

Comprehensive evaluation of typical planetary boundary layer (PBL) parameterization schemes in China. Part I: Understanding expressiveness of schemes for different regions from the mechanism perspective

Jia

Zhang

Wang

et al. 2023

Preprint

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Abstract. The optimal choice of the planetary boundary layer (PBL) parameterization scheme is of particular interest and urgency to a wide range of scholars, especially for many works involving models. At present, there have been many works to evaluate the PBL schemes. However, little research has been conducted into a more comprehensive and systematic assessment of the performance capability of schemes in key regions of China, especially when it comes to the differences in the mechanisms of the schemes themselves, primarily because there’s scarcely sufficient observational data, computer resources, and storage support to complete the work. In addition, there are many factors that influence the selection of schemes, such as underlying surface, initial and boundary conditions, near-surface layer scheme, horizontal/vertical resolution, etc. In this Part (i.e., Part I), four typical schemes (i.e., YSU, ACM2, BL and MYJ) are selected to systematically analyze and evaluate near-surface meteorological parameters, PBL vertical structure, PBL height (PBLH), and turbulent diffusion in five key regions (i.e., North China Plain, NCP; Yangtze River Delta, YRD; Sichuan Basin, SB; Pearl River Delta, PRD and Northwest Semi-arid, NS) of China in different seasons (i.e., January, April, July and October). The differences in the simulated 2-m temperatures between the nonlocal closure schemes are mainly affected by the downward shortwave radiation, but to compare the nonlocal closure schemes with the local closure schemes, the effect of sensible heat flux needs to be further considered. In terms of temporal variation, the simulated results for July are better than the other three months, and the simulated results for nighttime are better than daytime. In terms of regional distribution, the temperature at stations with higher elevation is easily underestimated, while overestimated with lower elevation. The variation of relative humidity corresponds to temperature. The 10-m wind speed is under the influence of factors like the momentum transfer coefficient and the integrated similarity functions at night. The wind speeds are more significantly overestimated in the plains and basin, while less overestimated or even underestimated in the mountains, as a result of the effect on topographic smoothing in the model. Moreover, the overestimation of small wind speeds at night is attributable to the inapplicability of the Monin-Obukhov similarity theory (MOST) at night. The model captures the vertical structure of temperature well, while the wind speed is outstandingly overestimated below 1000 m, largely because of the turbulent diffusion coefficient (TDC). The difference between the MOST and the mixing length theory, PBLH and Prandtl number is cited as the reason for the difference between the TDC of the YSU and ACM2 schemes. The TDCs of the BL and MYJ schemes are affected by the mixing length scale, which of BL is calculated on the basis of the effect of buoyancy, while MYJ calculates it with the consideration of the effect of the total turbulent kinetic energy. The PBLH of the BL scheme is better than the other schemes because of the better simulation results of temperature. The difference in the PBLH by the YSU and ACM2 scheme mainly comes from the Richardson number and the jagged PBLH of the MYJ scheme is due to the coarse vertical resolution and the threshold value. In general, to select the optimal scheme, it is necessary to offer different options for different regions with different focuses (heat or momentum). (1) Temperature field. The BL scheme is recommended for January in the NCP region, especially for Beijing, and the MYJ scheme is better for the other three months. The ACM2 scheme would be a good match for the YRD region, where the simulation differences between the four schemes are small. The topography of the SB region is more complex, but for most of the areas in the basin, the MYJ scheme is proposed, but if more stations outside the basin are involved, the BL scheme is recommended. The MYJ scheme is applied to the PRD region in January and April, and the BL scheme in July and October. The MYJ scheme is counselled for the NS region. (2) Wind field. The YSU scheme is recommended if the main concern is the near-surface layer, and the BL scheme is suggested if focusing on the variation in the vertical direction. The Part II will analyse and evaluate the factors that may influence the choice of the schemes and the results of model. The final evaluation of the parameterization scheme and uncertainties will lay the foundation for the improvement of the modules and forecasting of the GRAPES_CUACE regional model developed independently in China.

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Reanalysis profile downscaling with WRF model and sensitivity to PBL parameterization schemes over a subtropical station

Cited by 6 publications

References 82 publications

Precipitable Water Content Climatology over Poland

Precipitable Water Content Climatology over Poland

Optimization and Evaluation of the Weather Research and Forecasting (WRF) Model for Wind Energy Resource Assessment and Mapping in Iran

Comprehensive evaluation of typical planetary boundary layer (PBL) parameterization schemes in China. Part I: Understanding expressiveness of schemes for different regions from the mechanism perspective

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