scholarly journals The impact of periodization methods on the kinetic energy spectra for limited-area numerical weather prediction models

2014 ◽  
Vol 7 (5) ◽  
pp. 6489-6518
Author(s):  
V. Blažica ◽  
N. Gustafsson ◽  
N. Žagar
Keyword(s):  
Kinetic Energy ◽  
Discrete Cosine Transform ◽  
Numerical Weather Prediction ◽  
Prediction Models ◽  
Weather Prediction ◽  
Limited Area ◽  
Cosine Transform ◽  
Numerical Weather ◽  
Extension Zone ◽  
The Impact

Abstract. The paper deals with the comparison of the most common periodization methods used to obtain spectral fields of limited-area models for numerical weather prediction. The focus is on the impact the methods have on the spectra of the fields, which are used for verification and tuning of the models. A simplified model is applied with random fields that obey a known kinetic energy spectrum. The periodization methods under consideration are detrending, the discrete cosine transform and the application of an extension zone. For extension zone, three versions are applied: the Boyd method, the ALADIN method and the HIRLAM method. The results show that detrending and the discrete cosine transform have little impact on the spectra, as does the Boyd method for extension zone. For the ALADIN and HIRLAM methods, the impact depends on the width of the extension zone – the wider the zone, the more artificial energy and the larger impact on the spectra. The width of the extension zone correlates to the modifications in the shape of the spectra as well as to the amplitudes of the additional energy in the spectra.

scholarly journals The impact of periodization methods on the kinetic energy spectra for limited-area numerical weather prediction models

2015 ◽  
Vol 8 (1) ◽  
pp. 87-97 ◽  
Author(s):  
V. Blažica ◽  
N. Gustafsson ◽  
N. Žagar
Keyword(s):  
Kinetic Energy ◽  
Discrete Cosine Transform ◽  
Numerical Weather Prediction ◽  
Prediction Models ◽  
Weather Prediction ◽  
Limited Area ◽  
Cosine Transform ◽  
Numerical Weather ◽  
Extension Zone ◽  
The Impact

Abstract. The paper deals with the comparison of the most common periodization methods used to obtain spectral fields of limited-area models for numerical weather prediction. The focus is on the impact that the methods have on the spectra of the fields, which are used for verification and tuning of the models. A simplified model is applied with random fields that obey a known kinetic energy spectrum. The periodization methods under consideration are detrending, the discrete cosine transform and the application of an extension zone. For the extension zone, three versions are applied: the Boyd method, the ALADIN method and the HIRLAM method. The results show that detrending and the discrete cosine transform have little impact on the spectra, as does the Boyd method for extension zone. For the ALADIN and HIRLAM methods, the impact depends on the width of the extension zone – the wider the zone, the more artificial energy and the larger impact on the spectra. The width of the extension zone correlates to the modifications in the shape of the spectra as well as to the amplitudes of the additional energy in the spectra.

scholarly journals Sensitivity of Radiative Fluxes to Aerosols in the ALADIN-HIRLAM Numerical Weather Prediction System

2020 ◽  
Author(s):  
Laura Rontu ◽  
Emily Gleeson ◽  
Daniel Martin Perez ◽  
Kristian Pagh Nielsen ◽  
Velle Toll
Keyword(s):  
Optical Properties ◽  
Numerical Weather Prediction ◽  
Prediction Models ◽  
Weather Prediction ◽  
Limited Area ◽  
Prediction System ◽  
Heating Rates ◽  
Radiative Fluxes ◽  
Numerical Weather ◽  
The Impact

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 study 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 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 vertical distribution of the aerosol species. 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.

scholarly journals Understanding the model representation of clouds based on visible and infrared satellite observations

2021 ◽  
Vol 21 (16) ◽  
pp. 12273-12290
Author(s):  
Stefan Geiss ◽  
Leonhard Scheck ◽  
Alberto de Lozar ◽  
Martin Weissmann
Keyword(s):  
Numerical Weather Prediction ◽  
Satellite Images ◽  
Prediction Models ◽  
Weather Prediction ◽  
Satellite Observations ◽  
Limited Area ◽  
Infrared Observation ◽  
Numerical Weather ◽  
The Impact ◽  
Forward Operator

Abstract. There is a rising interest in improving the representation of clouds in numerical weather prediction models. This will directly lead to improved radiation forecasts and, thus, to better predictions of the increasingly important production of photovoltaic power. Moreover, a more accurate representation of clouds is crucial for assimilating cloud-affected observations, in particular high-resolution observations from instruments on geostationary satellites. These observations can also be used to diagnose systematic errors in the model clouds, which are influenced by multiple parameterisations with many, often not well-constrained, parameters. In this study, the benefits of using both visible and infrared satellite channels for this purpose are demonstrated. We focus on visible and infrared Meteosat SEVIRI (Spinning Enhanced Visible InfraRed Imager) images and their model equivalents computed from the output of the ICON-D2 (ICOsahedral Non-hydrostatic, development version based on version 2.6.1; Zängl et al., 2015) convection-permitting, limited area numerical weather prediction model using efficient forward operators. We analyse systematic deviations between observed and synthetic satellite images derived from semi-free hindcast simulations for a 30 d summer period with strong convection. Both visible and infrared satellite observations reveal significant deviations between the observations and model equivalents. The combination of infrared brightness temperature and visible reflectance facilitates the attribution of individual deviations to specific model shortcomings. Furthermore, we investigate the sensitivity of model-derived visible and infrared observation equivalents to modified model and visible forward operator settings to identify dominant error sources. Estimates of the uncertainty of the visible forward operator turned out to be sufficiently low; thus, it can be used to assess the impact of model modifications. Results obtained for various changes in the model settings reveal that model assumptions on subgrid-scale water clouds are the primary source of systematic deviations in the visible satellite images. Visible observations are, therefore, well-suited to constrain subgrid cloud settings. In contrast, infrared channels are much less sensitive to the subgrid clouds, but they can provide information on errors in the cloud-top height.

scholarly journals Sensitivity of Radiative Fluxes to Aerosols in the ALADIN-HIRLAM Numerical Weather Prediction System

Atmosphere ◽  
2020 ◽  
Vol 11 (2) ◽  
pp. 205
Author(s):  
Laura Rontu ◽  
Emily Gleeson ◽  
Daniel Martin Perez ◽  
Kristian Pagh Nielsen ◽  
Velle Toll
Keyword(s):  
Optical Properties ◽  
Real Time ◽  
Numerical Weather Prediction ◽  
Weather Prediction ◽  
Limited Area ◽  
Prediction System ◽  
Heating Rates ◽  
Radiative Fluxes ◽  
Numerical Weather ◽  
The Impact

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.

scholarly journals Operational Assimilation of GPS Zenith Total Delay Observations into the Met Office Numerical Weather Prediction Models

2012 ◽  
Vol 140 (8) ◽  
pp. 2706-2719 ◽  
Author(s):  
Gemma V. Bennitt ◽  
Adrian Jupp
Keyword(s):  
Numerical Weather Prediction ◽  
Prediction Models ◽  
Weather Prediction ◽  
Three Dimensional ◽  
Total Delay ◽  
Numerical Weather ◽  
Zenith Total Delay ◽  
Nwp Model ◽  
The Impact ◽  
Numerical Weather Prediction Models

Abstract Zenith total delay (ZTD) observations derived from ground-based GPS receivers have been assimilated operationally into the Met Office North Atlantic and European (NAE) numerical weather prediction (NWP) model since 2007. Assimilation trials were performed using the Met Office NAE NWP model at both 12- and 24-km resolution to assess the impact of ZTDs on forecasts. ZTDs were found generally to increase relative humidity in the analysis, increasing the humidity bias compared to radiosonde observations, which persisted through the forecasts at some vertical levels. Improvements to cloud forecasts were also identified. Assimilation of ZTDs using both three-dimensional and four-dimensional variational data assimilation (3D-Var/4D-Var) was investigated, and it is found that assimilation at 4D-Var does not deliver any clear benefit over 3D-Var in the periods studied with the NAE model. This paper summarizes the methods used to assimilate ZTDs at the Met Office and presents the results of impact trials performed prior to operational assimilation. Future improvements to the assimilation methods are discussed.

Numerical experiments with a parameterization of mires in the COSMO-D2 convection permitting limited-area numerical weather prediction framework

2020 ◽  
Author(s):  
Jürgen Helmert ◽  
Alla Yurova ◽  
Denis Blinov ◽  
Inna Rozinkina ◽  
Michael Baldauf ◽  
...  
Keyword(s):  
Numerical Weather Prediction ◽  
Numerical Experiments ◽  
Meteorological Parameters ◽  
Weather Prediction ◽  
Heat Diffusion ◽  
Limited Area ◽  
Lower Boundary Condition ◽  
Numerical Weather ◽  
Screen Level ◽  
The Impact

<p>Europe - especially the northern and middle latitudes - is one of Earth’s mire-rich regions. Among the main distribution areas for mires in Central Europe the coastal region along the southeastern corner of the North Sea (Frisia) shows the highest density of mires. Despite of the important role of mires acting as a carbon sink and modifying the Bowen ratio with influence on screen level meteorological parameters their adequate representation in land-surface schemes used in numerical weather prediction and climate models is still insufficient.</p><p>With the recent version 5.06 the COSMO model (Baldauf et al., 2017) offers a parameterization of mires based on Yurova et al. (2014). In this approach the heat diffusion in the vertical domain of the soil multilayer model TERRA is considered with modified equations describing the thermal conductivity for peat with given water/ice contents. The mire hydrology is parameterized by the solution of the Richard's equation in the vertical domain extended by the formulation of a lower boundary condition as a climatological layer of permanent saturation used to simulate the water table position, in conjunction with a mire‐specific evapotranspiration and runoff parameterization.</p><p>The impact of the mire parameterization on screen level meteorological parameters and mesoscale processes was investigated in two numerical experiments with COSMO-D2 in a convection permitting limited-area numerical weather prediction (NWP) framework for summer 2018 and winter 2018/2019.</p><p>We will present results from the objective verification system and discuss the impact of geospatial physiographic data for an improved representation of mires in the NWP framework.</p>

Calibrating the Tropospheric Delays of VLBI Observations using Numerical Weather Prediction Models

2021 ◽  
Author(s):  
Tobias Nilsson ◽  
Kyriakos Balidakis
Keyword(s):  
Numerical Weather Prediction ◽  
Prediction Models ◽  
Weather Prediction ◽  
External Information ◽  
Local Networks ◽  
Numerical Weather ◽  
Vlbi Data ◽  
The Impact ◽  
Tropospheric Delays ◽  
Numerical Weather Prediction Models

<p>The observations of geodetic Very Long Baseline Interferometry (VLBI) are affected by the troposphere, and this effect needs to be considered in the VLBI data analysis. The normal way of doing this is to estimate the zenith tropospheric delays and tropospheric gradients as additional parameter in the analysis. However, due to the poor geometric distributions of the observations in some VLBI sessions, like the Intensives, the tropospheric parameters cannot be estimated with a high accuracy. An alternative is to use external information on the tropospheric delay from Numerical Weather Prediction Models (NWM). Due to the increasing accuracy of the NWM, this alternative is becoming more and more interesting. In this work, we use tropospheric delays from the fifth ECMWF reanalysis, ERA5, in the analysis of VLBI data and evaluate the impacts on the results. We study the impact of different types of VLBI sessions, like Intensives, local networks, and global networks. The results of this study will show to what extent ERA5 data can be used to correct the tropospheric delays in geodetic VLBI. Furthermore, the results also give information on the accuracy of the tropospheric delays from NMW.</p>

scholarly journals Prediction of Air Temperature in the Polish Western Carpathian Mountains with the ALADIN-HIRLAM Numerical Weather Prediction System

Atmosphere ◽  
2019 ◽  
Vol 10 (4) ◽  
pp. 186 ◽  
Author(s):  
Piotr Sekula ◽  
Anita Bokwa ◽  
Bogdan Bochenek ◽  
Miroslaw Zimnoch
Keyword(s):  
Air Temperature ◽  
Numerical Weather Prediction ◽  
Prediction Models ◽  
Weather Prediction ◽  
Cold Season ◽  
Limited Area ◽  
Spatial And Temporal Variability ◽  
Carpathian Mountains ◽  
Statistical Validation ◽  
Numerical Weather

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.

scholarly journals Impact of Doppler Radar Wind Observations on Australian High-Resolution Numerical Weather Prediction

2020 ◽  
Vol 35 (2) ◽  
pp. 309-324
Author(s):  
Susan Rennie ◽  
Lawrence Rikus ◽  
Nathan Eizenberg ◽  
Peter Steinle ◽  
Monika Krysta
Keyword(s):  
High Resolution ◽  
Data Assimilation ◽  
Numerical Weather Prediction ◽  
Doppler Radar ◽  
Weather Prediction ◽  
Limited Area ◽  
Observation Error ◽  
Numerical Weather ◽  
Skill Scores ◽  
The Impact

Abstract The impact of Doppler radar wind observations on forecasts from a developmental, high-resolution numerical weather prediction (NWP) system is assessed. The new 1.5-km limited-area model will be Australia’s first such operational NWP system to include data assimilation. During development, the assimilation of radar wind observations was trialed over a 2-month period to approve the initial inclusion of these observations. Three trials were run: the first with no radar data, the second with radial wind observations from precipitation echoes, and the third with radial winds from both precipitation and insect echoes. The forecasts were verified against surface observations from automatic weather stations, against rainfall accumulations using fractions skill scores, and against satellite cloud observations. These methods encompassed verification across a range of vertical levels. Additionally, a case study was examined more closely. Overall results showed little statistical difference in skill between the trials, and the net impact was neutral. While the new observations clearly affected the forecast, the objective and subjective analyses showed a neutral impact on the forecast overall. As a first step, this result is satisfactory for the operational implementation. In future, upgrades to the radar network will start to reduce the observation error, and further improvements to the data assimilation are planned, which may be expected to improve the impact.

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