scholarly journals Semi-implicit semi-Lagrangian modelling of the atmosphere: a Met Office perspective

2016 ◽  
Vol 7 (3) ◽  
pp. 4-25 ◽  
Author(s):  
Tommaso Benacchio ◽  
Nigel Wood
Keyword(s):  
Numerical Weather Prediction ◽  
Prediction Models ◽  
Weather Prediction ◽  
Time Integration ◽  
Implicit Time ◽  
Good Representation ◽  
Solution Approach ◽  
Numerical Weather ◽  
Geostrophic Balance ◽  
The Impact

Abstract The semi-Lagrangian numerical method, in conjunction with semi-implicit time integration, provides numerical weather prediction models with numerical stability for large time steps, accurate modes of interest, and good representation of hydrostatic and geostrophic balance. Drawing on the legacy of dynamical cores at the Met Office, the use of the semi-implicit semi-Lagrangian method in an operational numerical weather prediction context is surveyed, together with details of the solution approach and associated issues and challenges. The numerical properties and performance of the current operational version of the Met Office’s numerical model are then investigated in a simplified setting along with the impact of different modelling choices.

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 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.

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.

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 Computational Efficiency Examination of a Regional Numerical Weather Prediction Model using KISTI Supercomputer NURION

2021 ◽  
Vol 12 (6) ◽  
pp. 743-749
Author(s):  
Ji-Sun Kang Et.al
Keyword(s):  
Prediction Model ◽  
Numerical Weather Prediction ◽  
Computational Efficiency ◽  
Prediction Models ◽  
Weather Prediction ◽  
Numerical Weather Prediction Model ◽  
Extreme Weather Events ◽  
Numerical Weather ◽  
Computational Performance ◽  
The Impact

For well-resolving extreme weather events, running numerical weather prediction model with high resolution in time and space is essential. We explore how efficiently such modeling could be, using NURION. We have examined one of community numerical weather prediction models, WRF, and KISTI’s 5th supercomputer NURION of national HPC. Scalability of the model has been tested at first, and we have compared the computational efficiency of hybrid openMP + MPI runs with pure MPI runs. In addition to those parallel computing experiments, we have tested a new storage layer called burst buffer to see whether it can accelerate frequent I/O. We found that there are significant differences between the computational environments for running WRF model. First of all, we have tested a sensitivity of computational efficiency to the number of cores per node. The sensitivity experiments certainly tell us that using all cores per node does not guarantee the best results, rather leaving several cores per node could give more stable and efficient computation. For the current experimental configuration of WRF, moreover, pure MPI runs gives much better computational performance than any hybrid openMP + MPI runs. Lastly, we have tested burst buffer storage layer that is expected to accelerate frequent I/O. However, our experiments show that its impact is not consistently positive. We clearly confirm the positive impact with relatively smaller problem size experiments while the impact was not seen with bigger problem experiments. Significant sensitivity to the different computational configurations shown this paper strongly suggests that HPC users should find out the best computing environment before massive use of their applications

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 Implementation of a semi-Lagrangian fully-implicit time integration of the unified soundproof system of equations for numerical weather prediction

2021 ◽  
Author(s):  
Abdessamad Qaddouri ◽  
Claude Girard ◽  
Syed Zahid Husain ◽  
Rabah Aider
Keyword(s):  
Numerical Weather Prediction ◽  
Weather Prediction ◽  
Time Integration ◽  
Implicit Time ◽  
System Of Equations ◽  
Dynamical Core ◽  
Vertical Coordinate ◽  
Numerical Weather ◽  
Fully Implicit ◽  
Computational Performance

AbstractAn alternate dynamical core that employs the unified equations of A. Arakawa and C.S. Konor (2009) has been developed within Environment and Climate change Canada’s GEM (Global Environmental Multiscale) atmospheric model. As in the operational GEM dynamical core, the novel core utilizes the same fully-implicit two-time-level semi-Lagrangian scheme for time discretization while the log-pressure-based terrain-following vertical coordinate has been slightly adapted. Overall, the new dynamical core implementation required only minor changes to the existing informatics code of the GEM model and from a computational performance perspective, the new core does not incur any significant additional cost. A broad range of tests – that include both two-dimensional idealized theoretical cases and three-dimensional deterministic forecasts covering both hydrostatic and non-hydrostatic scales–have been carried out to evaluate the performance of the new dynamical core. For all the tested cases, when compared to the operational GEM model, the new dynamical core based on the unified equations has been found to produce statistically equivalent results. These results imply that the unified equations can be adopted for operational numerical weather prediction that would employ a single soundproof system of equations to produce reliable forecasts for all meteorological scales of interest with negligible changes for the computational overhead.

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.

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