Performance analysis of weather research and forecasting model for simulating near-surface optical turbulence over land

Abstract The Weather Research and Forecasting Model permits finescale large-eddy simulations (LES) to be nested within coarser simulations, an approach that can generate more accurate turbulence statistics and improve other aspects of simulated flows. However, errors are introduced into the finer domain from the nesting methodology. Comparing nested domain, flat-terrain simulations of the neutral atmospheric boundary layer with single-domain simulations using the same mesh, but instead using periodic lateral boundary conditions, reveals the errors contributed to the nested solution from the parent domain and nest interfaces. Comparison of velocity spectra shows good agreement among higher frequencies, but greater power predicted on the nested domain at lower frequencies. Profiles of mean wind speed show significant near-surface deficits near the inflow boundaries, but equilibrate to improved values with distance. Profiles of the vertical flux of x momentum show significant underprediction by the nested domain close to the surface and near the inlet boundaries. While these underpredictions of the stresses, which cause the near-surface velocity deficits, attenuate with distance within the nested domains, significant errors remain throughout. Profiles of the resolved turbulence kinetic energy show considerable deviations from their single-domain values throughout the nested domains. The authors examine the accuracy of these parameters and their sensitivities to the turbulence subfilter stress model, mesh resolution, and grid aspect ratio, and provide guidance to practitioners of nested LES.

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Use of weather research and forecasting model outputs to obtain near-surface refractive index structure constant over the ocean

Optics Express ◽

10.1364/oe.24.013303 ◽

2016 ◽

Vol 24 (12) ◽

pp. 13303 ◽

Cited By ~ 14

Author(s):

Chun Qing ◽

Xiaoqing Wu ◽

Xuebin Li ◽

Wenyue Zhu ◽

Chunhong Qiao ◽

...

Keyword(s):

Refractive Index ◽

Structure Constant ◽

Index Structure ◽

Weather Research And Forecasting ◽

Forecasting Model ◽

Near Surface ◽

Weather Research

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Land-Use Improvements in the Weather Research and Forecasting Model over Complex Mountainous Terrain and Comparison of Different Grid Sizes

Boundary-Layer Meteorology ◽

10.1007/s10546-021-00617-1 ◽

2021 ◽

Author(s):

Alessio Golzio ◽

Silvia Ferrarese ◽

Claudio Cassardo ◽

Gugliemina Adele Diolaiuti ◽

Manuela Pelfini

Keyword(s):

Boundary Layer ◽

Land Use ◽

Land Cover ◽

Mixing Layer ◽

Local Area ◽

Heat Fluxes ◽

Weather Research And Forecasting ◽

Forecasting Model ◽

Mountainous Terrain ◽

Weather Research

AbstractWeather forecasts over mountainous terrain are challenging due to the complex topography that is necessarily smoothed by actual local-area models. As complex mountainous territories represent 20% of the Earth’s surface, accurate forecasts and the numerical resolution of the interaction between the surface and the atmospheric boundary layer are crucial. We present an assessment of the Weather Research and Forecasting model with two different grid spacings (1 km and 0.5 km), using two topography datasets (NASA Shuttle Radar Topography Mission and Global Multi-resolution Terrain Elevation Data 2010, digital elevation models) and four land-cover-description datasets (Corine Land Cover, U.S. Geological Survey land-use, MODIS30 and MODIS15, Moderate Resolution Imaging Spectroradiometer land-use). We investigate the Ortles Cevadale region in the Rhaetian Alps (central Italian Alps), focusing on the upper Forni Glacier proglacial area, where a micrometeorological station operated from 28 August to 11 September 2017. The simulation outputs are compared with observations at this micrometeorological station and four other weather stations distributed around the Forni Glacier with respect to the latent heat, sensible heat and ground heat fluxes, mixing-layer height, soil moisture, 2-m air temperature, and 10-m wind speed. The different model runs make it possible to isolate the contributions of land use, topography, grid spacing, and boundary-layer parametrizations. Among the considered factors, land use proves to have the most significant impact on results.

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Simulating the meteorology and PM10 concentrations in Arizona dust storms using the Weather Research and Forecasting model with Chemistry (Wrf-Chem)

Journal of the Air & Waste Management Association ◽

10.1080/10962247.2017.1357662 ◽

2018 ◽

Vol 68 (3) ◽

pp. 177-195 ◽

Cited By ~ 3

Author(s):

Peter Hyde ◽

Alex Mahalov ◽

Jialun Li

Keyword(s):

Dust Storms ◽

Weather Research And Forecasting ◽

Forecasting Model ◽

Weather Research

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Parallelization Strategies for the GPS Radio Occultation Data Assimilation with a Nonlocal Operator in the Weather Research and Forecasting Model

Journal of Atmospheric and Oceanic Technology ◽

10.1175/jtech-d-13-00195.1 ◽

2014 ◽

Vol 31 (9) ◽

pp. 2008-2014 ◽

Cited By ~ 2

Author(s):

Xin Zhang ◽

Ying-Hwa Kuo ◽

Shu-Ya Chen ◽

Xiang-Yu Huang ◽

Ling-Feng Hsiao

Keyword(s):

Data Assimilation ◽

Radio Occultation ◽

Weather Prediction ◽

Weather Research And Forecasting ◽

Forecasting Model ◽

Observation Operator ◽

Gps Radio Occultation ◽

Phase Observation ◽

Excess Phase ◽

Weather Research

Abstract The nonlocal excess phase observation operator for assimilating the global positioning system (GPS) radio occultation (RO) sounding data has been proven by some research papers to produce significantly better analyses for numerical weather prediction (NWP) compared to the local refractivity observation operator. However, the high computational cost and the difficulties in parallelization associated with the nonlocal GPS RO operator deter its application in research and operational NWP practices. In this article, two strategies are designed and implemented in the data assimilation system for the Weather Research and Forecasting Model to demonstrate the capability of parallel assimilation of GPS RO profiles with the nonlocal excess phase observation operator. In particular, to solve the parallel load imbalance problem due to the uneven geographic distribution of the GPS RO observations, round-robin scheduling is adopted to distribute GPS RO observations among the processing cores to balance the workload. The wall clock time required to complete a five-iteration minimization on a demonstration Antarctic case with 106 GPS RO observations is reduced from more than 3.5 h with a single processing core to 2.5 min with 106 processing cores. These strategies present the possibility of application of the nonlocal GPS RO excess phase observation operator in operational data assimilation systems with a cutoff time limit.

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