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

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

10.20944/preprints202001.0183.v1 ◽

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.

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

Geoscientific Model Development Discussions ◽

10.5194/gmdd-7-6489-2014 ◽

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.

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

Geoscientific Model Development ◽

10.5194/gmd-8-87-2015 ◽

2015 ◽

Vol 8 (1) ◽

pp. 87-97 ◽

Cited By ~ 4

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.

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Measuring the impact of additional instrumentation on the skill of numerical weather prediction models at forecasting wind ramp events during the first Wind Forecast Improvement Project (WFIP)

Wind Energy ◽

10.1002/we.2347 ◽

2019 ◽

Cited By ~ 4

Author(s):

Elena Akish ◽

Laura Bianco ◽

Irina V. Djalalova ◽

James M. Wilczak ◽

Joseph B. Olson ◽

...

Keyword(s):

Numerical Weather Prediction ◽

Prediction Models ◽

Weather Prediction ◽

Improvement Project ◽

Numerical Weather ◽

Ramp Events ◽

The Impact ◽

Numerical Weather Prediction Models

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

Atmosphere ◽

10.3390/atmos11020205 ◽

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.

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Assimilation of Satellite Cloud and Precipitation Observations in Numerical Weather Prediction Models: Introduction to the JAS Special Collection

Journal of the Atmospheric Sciences ◽

10.1175/2007jas2622.1 ◽

2007 ◽

Vol 64 (11) ◽

pp. 3737-3741 ◽

Cited By ~ 23

Author(s):

Ronald M. Errico ◽

George Ohring ◽

Fuzhong Weng ◽

Peter Bauer ◽

Brad Ferrier ◽

...

Keyword(s):

Numerical Weather Prediction ◽

Prediction Models ◽

Weather Forecasting ◽

International Workshop ◽

Weather Prediction ◽

Satellite Observations ◽

Atmospheric Sciences ◽

Numerical Weather ◽

Special Collection ◽

Numerical Weather Prediction Models

Abstract To date, the assimilation of satellite measurements in numerical weather prediction (NWP) models has focused on the clear atmosphere. But satellite observations in the visible, infrared, and microwave provide a great deal of information on clouds and precipitation. This special collection describes how to use this information to initialize clouds and precipitation in models. Since clouds and precipitation often occur in sensitive regions for forecast impacts, such improvements are likely necessary for continuing to acquire significant gains in weather forecasting. This special collection of the Journal of the Atmospheric Sciences is devoted to articles based on papers presented at the International Workshop on Assimilation of Satellite Cloud and Precipitation Observations in Numerical Weather Prediction Models, in Lansdowne, Virginia, in May 2005. This introduction summarizes the findings of the workshop. The special collection includes review articles on satellite observations of clouds and precipitation (Stephens and Kummerow), parameterizations of clouds and precipitation in NWP models (Lopez), radiative transfer in cloudy/precipitating atmospheres (Weng), and assimilation of cloud and precipitation observations (Errico et al.), as well as research papers on these topics.

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

Monthly Weather Review ◽

10.1175/mwr-d-11-00156.1 ◽

2012 ◽

Vol 140 (8) ◽

pp. 2706-2719 ◽

Cited By ~ 86

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.

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

10.5194/egusphere-egu2020-17891 ◽

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

Europe - especially the northern and middle latitudes - is one of Earth&#8217;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.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&#8208;specific evapotranspiration and runoff parameterization.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.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.

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

10.5194/egusphere-egu21-11956 ◽

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

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.

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