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Keywords = ALADIN-HIRLAM numerical weather prediction system

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27 pages, 597 KiB  
Article
Sensitivity of Radiative Fluxes to Aerosols in the ALADIN-HIRLAM Numerical Weather Prediction System
by Laura Rontu, Emily Gleeson, Daniel Martin Perez, Kristian Pagh Nielsen and Velle Toll
Atmosphere 2020, 11(2), 205; https://doi.org/10.3390/atmos11020205 - 14 Feb 2020
Cited by 9 | Viewed by 4926
Abstract
The direct radiative effect of aerosols is taken into account in many limited-area numerical weather prediction models using wavelength-dependent aerosol optical depths of a range of aerosol species. We studied the impact of aerosol distribution and optical properties on radiative transfer, based on [...] Read more.
The direct radiative effect of aerosols is taken into account in many limited-area numerical weather prediction models using wavelength-dependent aerosol optical depths of a range of aerosol species. We studied the impact of aerosol distribution and optical properties on radiative transfer, based on climatological and more realistic near real-time aerosol data. Sensitivity tests were carried out using the single-column version of the ALADIN-HIRLAM numerical weather prediction system, set up to use the HLRADIA simple broadband radiation scheme. The tests were restricted to clear-sky cases to avoid the complication of cloud–radiation–aerosol interactions. The largest differences in radiative fluxes and heating rates were found to be due to different aerosol loads. When the loads are large, the radiative fluxes and heating rates are sensitive to the aerosol inherent optical properties and the vertical distribution of the aerosol species. In such cases, regional weather models should use external real-time aerosol data for radiation parametrizations. Impacts of aerosols on shortwave radiation dominate longwave impacts. Sensitivity experiments indicated the important effects of highly absorbing black carbon aerosols and strongly scattering desert dust. Full article
(This article belongs to the Special Issue Aerosol Radiative Effects)
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27 pages, 6868 KiB  
Article
Prediction of Air Temperature in the Polish Western Carpathian Mountains with the ALADIN-HIRLAM Numerical Weather Prediction System
by Piotr Sekula, Anita Bokwa, Bogdan Bochenek and Miroslaw Zimnoch
Atmosphere 2019, 10(4), 186; https://doi.org/10.3390/atmos10040186 - 5 Apr 2019
Cited by 20 | Viewed by 4729
Abstract
Prediction of spatial and temporal variability of air temperature in areas with complex topography is still a challenge for numerical weather prediction models. Simulation of atmosphere over complex terrain requires dense and accurate horizontal and vertical grids. In this study, verification results of [...] Read more.
Prediction of spatial and temporal variability of air temperature in areas with complex topography is still a challenge for numerical weather prediction models. Simulation of atmosphere over complex terrain requires dense and accurate horizontal and vertical grids. In this study, verification results of three configurations of the Aire Limitée Adaptation Dynamique Développement International High-Resolution Limited Area Model (ALADIN-HIRLAM) numerical weather prediction (NWP) system, using two different horizontal and vertical resolutions and applied to the Polish Western Carpathian Mountains, are presented. One model of the ALADIN-HIRLAM NWP system is tested in two horizontal and vertical resolutions. Predicted air temperatures are compared with observations from stations located in different orographies. A comparison of model results with observations was conducted for three cold season intervals in 2017 and 2018. Statistical validation of model output demonstrates better model representativeness for stations located on hill and mountain tops compared to locations in valley bottoms. A comparison of results for two topography representations (2 × 2 km and 1 × 1 km) showed no statistically significant differences of root mean square error (RMSE) and bias between model results and observations. Full article
(This article belongs to the Section Meteorology)
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