scholarly journals Evaluation of high-resolution forecasts with the non-hydrostaticnumerical weather prediction model Lokalmodell for urban air pollutionepisodes in Helsinki, Oslo and Valencia

2006 ◽  
Vol 6 (8) ◽  
pp. 2107-2128 ◽  
Author(s):  
B. Fay ◽  
L. Neunhäuserer
Keyword(s):  
Prediction Model ◽  
Meteorological Parameters ◽  
Weather Prediction ◽  
Atmospheric Stability ◽  
Model Performance ◽  
Late Summer ◽  
Horizontal Resolution ◽  
Urban Air ◽  
Wind Speeds ◽  
Physiographic Parameters

Abstract. The operational numerical weather prediction model Lokalmodell LM with 7 km horizontal resolution was evaluated for forecasting meteorological conditions during observed urban air pollution episodes. The resolution was increased to experimental 2.8 km and 1.1 km resolution by one-way interactive nesting without introducing urbanisation of physiographic parameters or parameterisations. The episodes examined are two severe winter inversion-induced episodes in Helsinki in December 1995 and Oslo in January 2003, three suspended dust episodes in spring and autumn in Helsinki and Oslo, and a late-summer photochemical episode in the Valencia area. The evaluation was basically performed against observations and radiosoundings and focused on the LM skill at forecasting the key meteorological parameters characteristic for the specific episodes. These included temperature inversions, atmospheric stability and low wind speeds for the Scandinavian episodes and the development of mesoscale recirculations in the Valencia area. LM forecasts often improved due to higher model resolution especially in mountainous areas like Oslo and Valencia where features depending on topography like temperature, wind fields and mesoscale valley circulations were better described. At coastal stations especially in Helsinki, forecast gains were due to the improved physiographic parameters (land fraction, soil type, or roughness length). The Helsinki and Oslo winter inversions with extreme nocturnal inversion strengths of 18°C were not sufficiently predicted with all LM resolutions. In Helsinki, overprediction of surface temperatures and low-level wind speeds basically led to underpredicted inversion strength. In the Oslo episode, the situation was more complex involving erroneous temperature advection and mountain-induced effects for the higher resolutions. Possible explanations include the influence of the LM treatment of snow cover, sea ice and stability-dependence of transfer and diffusion coefficients. The LM simulations distinctly improved for winter daytime and nocturnal spring and autumn inversions and showed good skill at forecasting further episode-relevant meteorological parameters. The evaluation of the photochemical Valencia episode concentrated on the dominating mesoscale circulation patterns and showed that the LM succeeds well in describing all the qualitative features observed in the region. LM performance in forecasting the examined episodes thus depends on the key episode characteristics and also the season of the year with a need to improve model performance in very stable inversion conditions not only for urban simulations.

scholarly journals Evaluation of very high-resolution simulations with the non-hydrostatic numerical weather prediction model Lokalmodell for urban air pollution episodes in Helsinki, Oslo and Valencia

2005 ◽  
Vol 5 (5) ◽  
pp. 8233-8284 ◽  
Author(s):  
B. Fay ◽  
L. Neunhäuserer
Keyword(s):  
Air Pollution ◽  
Meteorological Parameters ◽  
Weather Prediction ◽  
Urban Air Pollution ◽  
Numerical Weather Prediction Model ◽  
Urban Air ◽  
Urban Air Pollution Episodes ◽  
Air Pollution Episodes ◽  
Physiographic Parameters ◽  
Pollution Episodes

Abstract. The operational numerical weather prediction model Lokalmodell LM with 7 km horizontal resolution was evaluated for simulations of the meteorological conditions during observed urban air pollution episodes. The resolution was increased to experimental 2.8 km and 1.1 km resolution by one-way interactive nesting without introducing urbanisation of physiographic parameters or parameterisations. The episodes examined are two severe winter inversion-induced episodes in Helsinki in December 1995 and Oslo in January 2003, three suspended dust episodes in spring and autumn in Helsinki and Oslo, and a late-summer photochemical episode in the Valencia area. The evaluation was basically performed against observations and radiosoundings and focused on the LM skill at forecasting the key meteorological parameters characteristic for the specific episodes. These included temperature inversions, atmospheric stability and low wind speed for the Scandinavian episodes and the development of mesoscale recirculations in the Valencia area. LM forecasts often improved due to higher model resolution especially in mountainous areas like Oslo and Valencia where features depending on topography like temperature, wind fields and mesoscale valley circulations were better described. At coastal stations especially in Helsinki, forecast gains were due to the improved physiographic parameters (land fraction, soil type, or roughness length). The Helsinki and Oslo winter inversions with extreme nocturnal inversion strengths of 18°C were not sufficiently predicted with all LM resolutions. In Helsinki, overprediction of surface temperatures and low-level wind speeds basically led to underpredicted inversion strength. In the Oslo episode, the situation was more complex involving erroneous temperature advection and mountain-induced effects for the higher resolutions. Possible explanations include the influence of the LM treatment of snow cover, sea ice and stability-dependence of transfer and diffusion coefficients. The LM simulations distinctly improved for winter daytime and nocturnal spring and autumn inversions and showed good skill at forecasting further episode-relevant meteorological parameters. The evaluation of the photochemical Valencia episode concentrated on the dominating mesoscale circulation patterns and showed that the LM succeeds well in describing all the qualitative features observed in the region. LM performance in forecasting the examined episodes thus depends on the key episode characteristics and also the season of the year with a need to improve model performance in very stable inversion conditions not only for urban simulations.

scholarly journals Verification of Forecast Weather Surface Variables over Vietnam Using the National Numerical Weather Prediction System

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Tien Du Duc ◽  
Lars Robert Hole ◽  
Duc Tran Anh ◽  
Cuong Hoang Duc ◽  
Thuy Nguyen Ba
Keyword(s):  
Numerical Weather Prediction ◽  
Weather Prediction ◽  
Model Performance ◽  
Wrf Model ◽  
Horizontal Resolution ◽  
Prediction System ◽  
Regional Models ◽  
Global Spectral Model ◽  
Numerical Weather ◽  
The Us

The national numerical weather prediction system of Vietnam is presented and evaluated. The system is based on three main models, namely, the Japanese Global Spectral Model, the US Global Forecast System, and the US Weather Research and Forecasting (WRF) model. The global forecast products have been received at 0.25- and 0.5-degree horizontal resolution, respectively, and the WRF model has been run locally with 16 km horizontal resolution at the National Center for Hydro-Meteorological Forecasting using lateral conditions from GSM and GFS. The model performance is evaluated by comparing model output against observations of precipitation, wind speed, and temperature at 168 weather stations, with daily data from 2010 to 2014. In general, the global models provide more accurate forecasts than the regional models, probably due to the low horizontal resolution in the regional model. Also, the model performance is poorer for stations with altitudes greater than 500 meters above sea level (masl). For tropical cyclone performance validations, the maximum wind surface forecast from global and regional models is also verified against the best track of Joint Typhoon Warning Center. Finally, the model forecast skill during a recent extreme rain event in northeast Vietnam is evaluated.

Global NWP Modeling of urban environments at ~1km resolution

2021 ◽  
Author(s):  
Joe McNorton ◽  
Nicolas Bousserez ◽  
Gabriele Arduini ◽  
Anna Agusti-Panareda ◽  
Gianpaolo Balsamo ◽  
...  
Keyword(s):  
Land Surface ◽  
Urban Areas ◽  
Weather Prediction ◽  
Model Performance ◽  
Horizontal Resolution ◽  
Urban Environments ◽  
Trace Gas Emissions ◽  
Urban Representation ◽  
Forecasting System ◽  
Future Work

<p>Urban areas make up only a small fraction of the Earth’s surface; however, they are home to over 50% of the global population. Accurate numerical weather prediction (NWP) forecasts in these areas offer clear societal benefits; however, land-atmosphere interactions are significantly different between urban and non-urban environments. Forecasting urban weather requires higher model resolution than the size of the urban domain, which is often achievable by regional but not global NWP models. Here we present the preliminary implementation of an urban scheme within the land surface component of the global Integrated Forecasting System (IFS), at recently developed ~1km horizontal resolution. We evaluate the representation error of fluxes and NWP variables at coarser resolutions (~9 km and ~31 km), using the high resolution as truth. We evaluate the feasibility of the scheme and its urban representation at ~1km scales. Availability of urban mapping data limit the affordable complexity of the global scheme; however, using generalisations model performance is improved over urban sites, even adopting simple schemes, and the modelled Urban Heat Island effects show broad agreement with observations. Several directions for future work are explored including a more complex urban representation, restructuring of the urban tiling and the introduction of an urban emissions model for trace gas emissions.<strong> </strong></p>

Convection is key to better polar low forecasts

2020 ◽  
Author(s):  
Matilda Hallerstig ◽  
Linus Magnusson ◽  
Erik Kolstad
Keyword(s):  
Prediction Models ◽  
Deterministic Model ◽  
Rapid Development ◽  
Weather Prediction ◽  
Model Performance ◽  
Horizontal Resolution ◽  
Added Value ◽  
Grid Spacing ◽  
Polar Lows ◽  
Polar Low

<p>ECMWF HRES and Arome Arctic are the operational Numerical Weather Prediction models that forecasters in northern Norway use to predict Polar lows in the Nordic and Barents Seas. These type of lows are small, but intense mesoscale cyclones with strong, gusty winds and heavy snow showers. They cause hazards like icing, turbulence, high waves and avalanches that threaten offshore activity and coastal societies in the area. Due to their small size and rapid development, medium range global models with coarser resolutions such as ECMWF have not been able to represent them properly. This was only possible with short range high resolution regional models like Arome. When ECMWF introduced their new HRES deterministic model with 9 km grid spacing, the potential for more precise polar low forecasts increased. Here we use case studies and sensitivity tests to examine the ability of ECMWF HRES to represent polar lows. We also evaluate what added value the Arome Arctic model with 2.5 km grid spacing gives. For verification, we use coastal meteorological stations and scatterometer winds. We found that convection has a greater impact on model performance than horizontal resolution. We also see that Arome Arctic produces higher wind speeds than ECMWF HRES. To improve performance during polar lows for models with a horizontal grid spacing less than 10 km, it is therefore more important to improve the understanding and formulation of convective processes rather than simply increasing horizontal resolution.</p>

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