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Atmosphere
Special Issues
Wind Forecasting over Complex Terrain
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Wind Forecasting over Complex Terrain

A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Meteorology".

Deadline for manuscript submissions: closed (1 July 2023) | Viewed by 8239

Special Issue Editor

Dr. Richard Turner

E-Mail Website
Guest Editor
Meteorology and Remote Sensing, NIWA, Wellington 6021, New Zealand
Interests: extreme winds; wind flow modelling; atmospheric dispersion

Special Issue Information

Dear Colleagues,

Accurately forecasting the weather and winds over complex terrain has important applications, such as forecasting for wind farms, fire-spread modelling, estimation of pollutant and pathogen dispersion, and impacts on infrastructure, such as high-voltage overhead electrical grids and long-span bridges. Additionally, for regions where orographic rainfall is important, the representation of the underlying complex terrain and physical processes that influence flow over and around the terrain can greatly influence the accuracy of rainfall forecasts. This has impacts on downstream forecasts of river stream flows and flooding and ultimately emergency response decisions.

The advent of convective-scale weather models (i.e., grid spacing ~1 km) over the last decade has seen great improvements in forecast accuracy over regions of complex terrain, but several challenges remain. These can include the availability of suitable high-resolution topographic datasets for use in the models, the applicability of orographic drag parameterisation schemes not originally designed to work at the convective scale, and the numerical stability of the models when the orographic slopes in the model become ever steeper. The introduction of sub-km resolution city-scale models (~100–300 m grid spacing) is also highlighting new challenges, particularly around the (lack of) representation of turbulence processes that become more relevant at these resolutions. With ever increasing computational resources available to researchers, understanding these issues is critical to the pursuit of ever more accurate wind forecasting.

In this planned Special Issue of Atmosphere on “Wind Forecasting over Complex Terrain”, the focus will be on what and how these challenges are being addressed. As such, the focus will not only be on recent advances in numerical schemes, improved ancillary information, and models that more accurately represent the details of wind flows over complex terrain, but also advances in downscaling tools (including machine learning/artificial intelligence) that could increase the efficiency and interpretation of model results and improve site-specific and “gridded MOS” forecasts of winds and other key weather variables. Additionally, submissions will be sought on the communication of wind warnings and the challenges faced by forecasters and forecast users in situations where there are large variations in forecast wind flows due to the complexity of the terrain.

The purpose of this Special Issue is to increase the profile of recent advances in wind forecasting over complex terrain and aid the uptake of improved methods in the scientific/research and forecasting/operational disciplines.

Dr. Richard Turner
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Atmosphere is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • wind forecasts 
  • complex terrain
  • turbulence and dispersion 
  • downscaling
  • wind gusts 
  • wind power 
  • weather forecasts

Published Papers (6 papers)

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Research

15 pages, 5532 KiB  
Article
Characteristics and Establishment of Objective Identification Criteria and Predictors for Foehn Winds in Urumqi, China
by Maoling Ayitikan, Xia Li, Qing He, Yusufu Musha, Hao Tang, Shuting Li, Yuting Zhong and Gang Ren
Atmosphere 2023, 14(8), 1206; https://doi.org/10.3390/atmos14081206 - 27 Jul 2023
Viewed by 642
Abstract
The special terrain of Urumqi (in the valley area) often triggers strong foehn winds, causing huge losses to local people’s lives and social economies. By using the surface observation data of the hourly temperature, pressure, humidity, and wind from the downwind Urumqi Meteorological [...] Read more.
The special terrain of Urumqi (in the valley area) often triggers strong foehn winds, causing huge losses to local people’s lives and social economies. By using the surface observation data of the hourly temperature, pressure, humidity, and wind from the downwind Urumqi Meteorological Station and the upwind Dabancheng Meteorological Station in the Middle Tianshan Canyon and the NCEP/NCAR reanalysis data during 2008–2022, this paper establishes the dataset of foehn processes at Urumqi Station in the past 15 years and analyzes the variation rules of the associated meteorological variables during the foehn processes. In addition, based on the physical mechanism of the occurrence of foehn, a three-element identification criterion (i.e., 94° ≤ 2 min average wind direction ≤ 168°, 2 min average wind speed ≥ 2.0 m/s, and Δθ between Urumqi station and Dabancheng station ≥ 0.29 K) for foehn in Urumqi is established by comparing and analyzing the variations of wind direction (WD), wind speed (WS), and the potential temperature difference (Δθ) between the two weather stations during the periods of foehn and non-foehn winds from 2013 to 2022. In addition, the performance of the three-element identification criterion is verified, and the results suggest that this criterion has an accuracy of 82.96% and a hit rate of 89.50% for the 2008–2012 foehn events in Urumqi. Moreover, the hit rate of this criterion for foehn wind of gale or above level (i.e., a 2 min wind ≥ 10.8 m/s on average) is 100%. In addition, combined with two predictors of sea-level pressure difference (ΔP) and Δθ between downwind stations and upwind stations, the foehn forecast can be more accurate than that provided by a single predictor. With ΔP ≤ −12 hPa and Δθ ≥ 5 K, the chances for foehn to occur are over 90%. This finding would have some reference and application values for the foehn forecasting. Full article
(This article belongs to the Special Issue Wind Forecasting over Complex Terrain)
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13 pages, 2740 KiB  
Article
Short-Term Wind Speed Forecasting Based on the EEMD-GS-GRU Model
by Huaming Yao, Yongjie Tan, Jiachen Hou, Yaru Liu, Xin Zhao and Xianxun Wang
Atmosphere 2023, 14(4), 697; https://doi.org/10.3390/atmos14040697 - 07 Apr 2023
Cited by 1 | Viewed by 1448
Abstract
To improve the accuracy of short-term wind speed forecasting, we proposed a Gated Recurrent Unit network forecasting method, based on ensemble empirical mode decomposition and a Grid Search Cross Validation parameter optimization algorithm. In this study, first, in the process of decomposing, the [...] Read more.
To improve the accuracy of short-term wind speed forecasting, we proposed a Gated Recurrent Unit network forecasting method, based on ensemble empirical mode decomposition and a Grid Search Cross Validation parameter optimization algorithm. In this study, first, in the process of decomposing, the set empirical mode of decomposition was introduced to divide the wind time series into high-frequency modal, low-frequency modal, and trend modal, using the Pearson correlation coefficient. Second, during parameter optimization, the grid parameter optimization algorithm was employed in the GRU model to search for the combination of optimal parameters. Third, the improved GRU model was driven with the decomposed components to predict the new components, which were used to obtain the predicted wind speed by modal reorganization. Compared with other models (i.e., the LSTM, GS-LSTM, EEMD-LSTM, and the EEMD-GS-LSTM), the proposed model was applied to the case study on wind speed of a wind farm, located in northwest China. The results showed that the presented forecasting model could reduce the forecasting error (RMSE) from 1.411 m/s to 0.685 m/s and can improve the accuracy of forecasts. This model provides a new approach for short-term wind speed forecasting. Full article
(This article belongs to the Special Issue Wind Forecasting over Complex Terrain)
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14 pages, 15336 KiB  
Article
Turbulent Inflow Generation for Large-Eddy Simulation of Winds around Complex Terrain
by Inanc Senocak and Rey DeLeon
Atmosphere 2023, 14(3), 447; https://doi.org/10.3390/atmos14030447 - 23 Feb 2023
Viewed by 1251
Abstract
Accurate turbulent inflow conditions are needed to broaden the application of the large-eddy simulation technique to predict winds around arbitrarily complex terrain. We investigate the concept of buoyancy perturbations with colored noise to trigger turbulence in upstream flows approaching complex terrain regions. Random [...] Read more.
Accurate turbulent inflow conditions are needed to broaden the application of the large-eddy simulation technique to predict winds around arbitrarily complex terrain. We investigate the concept of buoyancy perturbations with colored noise to trigger turbulence in upstream flows approaching complex terrain regions. Random perturbations are imposed on the source term in the pseudo-temperature transport equation. These perturbations are effective within three-dimensional boxes and scaled using a bulk Richardson number defined for each box. We apply the turbulent inflow generation technique to predict winds around the Askervein and Bolund Hills under neutrally stratified conditions. We find that a common value for the bulk Richardson number works well for a variety of flow problems. Additionally, we show that the height of the perturbation box plays an important role in the accuracy of the predictions around complex terrain. We consistently obtained good results for both simulation cases when the perturbation box height was made a fraction of the Obukhov length scale. Full article
(This article belongs to the Special Issue Wind Forecasting over Complex Terrain)
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14 pages, 5467 KiB  
Article
Medium- and Long-Term Wind-Power Forecasts, Considering Regional Similarities
by Xianxun Wang, Yaru Liu, Jiachen Hou, Suoping Wang and Huaming Yao
Atmosphere 2023, 14(3), 430; https://doi.org/10.3390/atmos14030430 - 21 Feb 2023
Cited by 4 | Viewed by 1341
Abstract
Accurate and efficient medium- and long-term forecasts of wind power can provide technical support for the efficient development and utilization of wind resources. Considering the regional characteristics of wind resources, the regional-similarity factor was introduced into the study of wind-power forecasting, and, to [...] Read more.
Accurate and efficient medium- and long-term forecasts of wind power can provide technical support for the efficient development and utilization of wind resources. Considering the regional characteristics of wind resources, the regional-similarity factor was introduced into the study of wind-power forecasting, and, to assess the long-term dependence of wind power, the long-short-term-memory method was selected for medium- and long-term forecasting of wind-power trends in a case study carried out in Northwest China. The results showed that the forecasting error of the presented method was reduced by an average of 20.80%, compared with the forecasting of individual stations, which verified the effectiveness of considering the regional characteristics in wind-resource prediction. Different area-division methods resulted in different effects on prediction accuracy. This study provides a new approach and a reference for medium- and long-term wind-resource prediction. Full article
(This article belongs to the Special Issue Wind Forecasting over Complex Terrain)
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16 pages, 6045 KiB  
Article
Analysis of Gravity Wave Characteristics during a Hailstone Event in the Cold Vortex of Northeast China
by Xiujuan Wang, Lingkun Ran, Yanbin Qi, Zhongbao Jiang, Tian Yun and Baofeng Jiao
Atmosphere 2023, 14(2), 412; https://doi.org/10.3390/atmos14020412 - 20 Feb 2023
Cited by 1 | Viewed by 1163
Abstract
Based on high-resolution pressure data collected by a microbarograph and Fourier transform (FFT) data processing, a detailed analysis of the frequency spectra characteristics of gravity waves during a hailstone event in the cold vortex of Northeast China (NECV) on 9 September 2021 is [...] Read more.
Based on high-resolution pressure data collected by a microbarograph and Fourier transform (FFT) data processing, a detailed analysis of the frequency spectra characteristics of gravity waves during a hailstone event in the cold vortex of Northeast China (NECV) on 9 September 2021 is presented. The results show that the deep NECV served as the large-scale circulation background for the hailstone event. The development of hailstones was closely related to gravity waves. In different hail stages, the frequency spectra characteristics of gravity waves were obviously different. One and a half hours before hailfall, there were gravity wave precursors with periods of 50–180 min and corresponding amplitudes ranging from 30 to 60 Pa. During hailfall, the center amplitudes of the gravity waves were approximately 50 Pa and 60 Pa, with the corresponding period ranges expanding to 60–70 min and 160–240 min. Simultaneously, hailstones initiated shorter periods (26–34 min) of gravity waves, with the amplitudes increasing to approximately 12–18 Pa. The relationship between hailstones and gravity waves was positive. After hailfall, gravity waves weakened and dissipated rapidly. As shown by the reconstructed gravity waves, key periods of gravity wave precursors ranged from 50–180 min, which preceded hailstones by several hours. When convection developed, there was thunderstorm high pressure and an outflow boundary. The airflow converged and diverged downstream, resulting in the formation of gravity waves and finally triggering hailfall. Gravity wave predecessors are significant for hail warnings and artificial hail suppression. Full article
(This article belongs to the Special Issue Wind Forecasting over Complex Terrain)
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24 pages, 4920 KiB  
Article
Hong Kong Airport Wind Shear Now-Casting System Development and Evaluation
by Jenny Stocker, Kate Johnson, Rose Jackson, Stephen Smith, Daniel Connolly, David Carruthers and Pak-Wai Chan
Atmosphere 2022, 13(12), 2094; https://doi.org/10.3390/atmos13122094 - 13 Dec 2022
Cited by 2 | Viewed by 1372
Abstract
A wind-shear now-casting system for Hong Kong International Airport is described. The system has been configured and run retrospectively for the period from January to April 2018 at 20-min intervals using two sets of meteorological inputs to quantify uncertainty. Outputs from the system [...] Read more.
A wind-shear now-casting system for Hong Kong International Airport is described. The system has been configured and run retrospectively for the period from January to April 2018 at 20-min intervals using two sets of meteorological inputs to quantify uncertainty. Outputs from the system include calculations of headwind for the northerly and southerly runways at the airport. Six metrics have been defined that attempt to identify areas of strong wind shear; these involve quantification of headwind and headwind gradient in both the horizontal and vertical directions. Receiver operating characteristic (ROC) curves have been generated for all metrics, runways, and meteorological conditions using pilot wind-shear reports to define wind-shear events. These curves allow for derivation of metric thresholds that could be used within an operational system to provide wind-shear alerts. The skill of the system for the 4-month period was quantified in terms of the probability of detection (POD, ideal value 1.0) of wind-shear events; system performance was better for the southerly runway, with the majority of POD values in the range 0.6 to 0.8. Full article
(This article belongs to the Special Issue Wind Forecasting over Complex Terrain)
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