Impact of Lidar Data Assimilation on Low-Level Wind Shear Simulation at Lanzhou Zhongchuan International Airport, China: A Case Study

Li, Lanqian; Xie, Ningjing; Fu, Longyan; Zhang, Kaijun; Shao, Aimei; Yang, Yi; Ren, Xinfeng

doi:10.3390/atmos11121342

Cited by 5 publications

(2 citation statements)

References 27 publications

(41 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…There are a number of studies showing the benefits of data assimilation (DA) for low‐level wind forecasts using real observations from a single wind‐profiling instrument (Sawada et al ., 2015; Pichugina et al ., 2017; Finn et al ., 2020; Li et al ., 2020; Hristova‐Veleva et al ., 2021). For operational DA, however, it is beneficial to build a dense network of remote‐sensing sites capable of continuous profiling of wind in the atmospheric boundary layer (ABL).…”

Section: Introductionmentioning

confidence: 99%

Estimating the benefit of Doppler wind lidars for short‐term low‐level wind ensemble forecasts

Nomokonova

Griewank

Löhnert

et al. 2022

Quart J Royal Meteoro Soc

View full text Add to dashboard Cite

This work focuses on the potential of a network of Doppler lidars for the improvement of short‐term forecasts of low‐level wind. For the impact assessment, we developed a new methodology that is based on ensemble sensitivity analysis (ESA). In contrast to preceding network design studies using ESA, we calculate the explicit sensitivity including the inverse of the background covariance boldB$$ \mathbf{B} $$ matrix to account directly for the localization scale of the assimilation system. The new method is applied to a pre‐existing convective‐scale 1,000‐member ensemble simulation to mitigate effects of spurious correlations. We evaluate relative changes in the variance of a forecast metric, that is, the low‐level wind components averaged over the Rhein–Ruhr metropolitan area in Germany. This setup allows us to compare the relative variance change associated with the assimilation of hypothetical observations from a Doppler wind lidar with respect to the assimilation of surface‐wind observations only. Furthermore, we assess sensitivities of derived variance changes to a number of settings, namely observation errors, localization length scale, regularization factor, number of instruments in the network, and their location, as well as data availability of the lidar measurements. Our results demonstrate that a network of 20–30 Doppler lidars leads to a considerable variance reduction of the forecast metric chosen. On average, an additional network of 25 Doppler lidars can reduce the 1–3 hr forecast error by a factor of 1.6–3.3 with respect to 10‐m wind observations only. The results provide the basis for designing an operational network of Doppler lidars for the improvement of short‐term low‐level wind forecasts that could be especially valuable for the renewable energy sector.

show abstract

Section: Introductionmentioning

confidence: 99%

Estimating the benefit of Doppler wind lidars for short‐term low‐level wind ensemble forecasts

Nomokonova

Griewank

Löhnert

et al. 2022

Quart J Royal Meteoro Soc

View full text Add to dashboard Cite

show abstract

“…In addition, there are also several studies trying to simulate and predict LLWS using numerical prediction models as well as investigating the impact of the lidar data on LLWS numerical simulations [18,24,25]; however, encouraging results have not been achieved, and it is not currently applicable in routine operations.…”

Section: Introductionmentioning

confidence: 99%

Overview of Low-Level Wind Shear Characteristics over Chinese Mainland

et al. 2021

Self Cite

View full text Add to dashboard Cite

The characteristics of low-level wind shear (LLWS) over the Chinese mainland were investigated using reports from pilots, air traffic controllers and the number of arriving/departing flights from 2016 to 2020. A preliminary analysis of the impact of the flights on the LLWS reports was carried out, and the cause of LLWS was also investigated. LLWS reports from most airports indicate that LLWS is most likely to occur within 600 m AGL with a higher density below 300 m, but with some exceptions, as wind shear is reported at higher altitudes at some airports. Airports with a high frequency of LLWS reports are almost all located in or around regions with complex topography and in regions with prevailing weather conditions favorable to LLWS. The variation in overall LLWS reports displays a steady increase from 2016 to 2019 and a decrease from 2019 to 2020, consistent with the trend in the number of flights, but with no evidently similar trends for individual airports. Seasonal variations in LLWS reports are observed and demonstrate no notable impact caused by the number of flights, implying that the main cause is the monthly variation of weather conditions. Diurnal variation is also evident and largely associated with the variation in number of flights during the busy period in addition to weather conditions, such as common strong winds, in the afternoon.

show abstract

Numerical Simulation of Low-Level Wind Shear at Soekarno-Hatta Airport Associated with Landward Propagation of Mesoscale Convective System

Andarini¹,

Munandar

Fathrio³

2023

Springer Proceedings in Physics

View full text Add to dashboard Cite

Impact of Lidar Data Assimilation on Low-Level Wind Shear Simulation at Lanzhou Zhongchuan International Airport, China: A Case Study

Cited by 5 publications

References 27 publications

Estimating the benefit of Doppler wind lidars for short‐term low‐level wind ensemble forecasts

Estimating the benefit of Doppler wind lidars for short‐term low‐level wind ensemble forecasts

Overview of Low-Level Wind Shear Characteristics over Chinese Mainland

Numerical Simulation of Low-Level Wind Shear at Soekarno-Hatta Airport Associated with Landward Propagation of Mesoscale Convective System

Contact Info

Product

Resources

About