scholarly journals The use of GNSS zenith total delays in operational AROME/Hungary 3D-Var over a central European domain

2019 ◽  
Vol 12 (3) ◽  
pp. 1569-1579 ◽  
Author(s):  
Máté Mile ◽  
Patrik Benáček ◽  
Szabolcs Rózsa
Keyword(s):  
Data Assimilation ◽  
Numerical Weather Prediction ◽  
Bias Correction ◽  
Weather Prediction ◽  
Added Value ◽  
Limited Area ◽  
Central European ◽  
Numerical Weather ◽  
The Impact ◽  
Assimilation Scheme

Abstract. The delay of satellite signals broadcasted by Global Navigation Satellite System (GNSS) provides unique atmospheric observations which endorse numerical weather prediction from global to limited-area models. Due to the possibility of its frequent and near-real-time estimation, the zenith total delays (ZTDs) are valuable information for any state-of-the-art data assimilation system. This article introduces the data assimilation of ZTDs in a Hungarian numerical weather prediction system, which was carried out by taking into account observations from central European GNSS analysis and processing centres. The importance of ZTD observations is described and shown by a diagnostic tool in the 3-hourly updated 3D-Var assimilation scheme. Furthermore, observing system experiments are done to evaluate the impact of GNSS ZTDs on mesoscale limited-area forecasts. The results of the use of GNSS ZTDs showed a clear added value to improve screen-level temperature and humidity forecasts when the bias is accurately estimated and corrected in the data assimilation scheme. The importance of variational, i.e. adaptive bias correction, is highlighted by verification scores compared to static bias correction. Moreover, this paper reviews the quality control of GNSS ground-based stations inside the central European domain, the calculation of optimal thinning distance and the preparation of the two above-mentioned bias correction methods. Finally, conclusions are drawn on different settings of the forecast and analysis experiments with a brief future outlook.

scholarly journals The use of GNSS zenith total delays in operational AROME/Hungary 3D-Var over a Central European domain

2018 ◽  
Author(s):  
Máté Mile ◽  
Patrik Benáček ◽  
Szabolcs Rózsa
Keyword(s):  
Data Assimilation ◽  
Bias Correction ◽  
Weather Prediction ◽  
Time Estimation ◽  
Satellite System ◽  
Added Value ◽  
Limited Area ◽  
Central European ◽  
The Impact ◽  
Assimilation Scheme

Abstract. The delay of satellite signals broadcasted by Global Navigation Satellite System (GNSS) provides unique atmospheric observation which endorses numerial weather prediction from global to limited-area models. Due to the possibility of its frequent and near real-time estimation, the zenith total delays (ZTD) are valuable information for any state-of-the-art data assimilation systems. This article introduces the data assimilation of ZTDs in a Hungarian numerical weather prediction system which was carried out taking into account observations from Central-European GNSS analysis and processing centres. The importance of ZTD observations is described and showed by a diagnostic tool in the three hourly updated 3D-Var variational assimilation scheme. Furthermore, observing system experiments are done to evaluate the impact of GNSS ZTDs on mesoscale limited-area forecasts. The results of the use of GNSS ZTDs showed a clear added value to improve screen-level temperature and humidity forecasts when bias is accurately estimated and corrected in the data assimilation scheme. The importance of variational i.e. adaptive bias correction is highlighted by verification scores compared to static bias correction. Moreover, this paper reviews the quality control of GNSS ground-based stations inside the Central-European domain, the calculation of optimal thinning distance and the preparation of two above mentioned bias correction methods. At the end of this article, the conclusion is drawn about different settings of the forecast and analysis experiments with a brief future outlook.

scholarly journals Data assimilation of GNSS zenith total delays from a Nordic processing centre

2017 ◽  
Vol 17 (22) ◽  
pp. 13983-13998 ◽  
Author(s):  
Magnus Lindskog ◽  
Martin Ridal ◽  
Sigurdur Thorsteinsson ◽  
Tong Ning
Keyword(s):  
Data Assimilation ◽  
Numerical Weather Prediction ◽  
Bias Correction ◽  
Weather Prediction ◽  
Satellite System ◽  
Initial State ◽  
Numerical Weather ◽  
Processing Centre ◽  
The Impact ◽  
Forecast Quality

Abstract. Atmospheric moisture-related information estimated from Global Navigation Satellite System (GNSS) ground-based receiver stations by the Nordic GNSS Analysis Centre (NGAA) have been used within a state-of-the-art kilometre-scale numerical weather prediction system. Different processing techniques have been implemented to derive the moisture-related GNSS information in the form of zenith total delays (ZTDs) and these are described and compared. In addition full-scale data assimilation and modelling experiments have been carried out to investigate the impact of utilizing moisture-related GNSS data from the NGAA processing centre on a numerical weather prediction (NWP) model initial state and on the ensuing forecast quality. The sensitivity of results to aspects of the data processing, station density, bias-correction and data assimilation have been investigated. Results show benefits to forecast quality when using GNSS ZTD as an additional observation type. The results also show a sensitivity to thinning distance applied for GNSS ZTD observations but not to modifications to the number of predictors used in the variational bias correction applied. In addition, it is demonstrated that the assimilation of GNSS ZTD can benefit from more general data assimilation enhancements and that there is an interaction of GNSS ZTD with other types of observations used in the data assimilation. Future plans include further investigation of optimal thinning distances and application of more advanced data assimilation techniques.

scholarly journals Data assimilation of GNSS Zenith Total Delays from a Nordic processing centre

2017 ◽  
Author(s):  
Magnus Lindskog ◽  
Martin Ridal ◽  
Sigurdur Thorsteinsson ◽  
Tong Ning
Keyword(s):  
Data Assimilation ◽  
Numerical Weather Prediction ◽  
Bias Correction ◽  
Weather Prediction ◽  
Satellite System ◽  
Initial State ◽  
Numerical Weather ◽  
Processing Centre ◽  
The Impact ◽  
Forecast Quality

Abstract. Atmospheric moisture-related information obtained from Global Navigation Satellite System (GNSS) observations from ground-based receiver stations of the Nordic GNSS Analysis Centre (NGAA) have been used within a state-of-the-art km-scale numerical weather prediction system. Different processing techniques have been implemented to derive the the moisture-related GNSS information in the form of Zenith Total Delays (ZTD) and these are described and compared. In addition full scale data assimilation and modelling experiments have been carried out to investigate the impact of utilizing moisture related GNSS data from the NGAA processing centre on a numerical weather prediction (NWP) model initial state and on the following forecast quality. The sensitivity of results to aspects of the data processing, observation density, bias-correction and data assimilation have been investigated. Results show a benefit on forecast quality of using GNSS ZTD as an additional observation type. The results also show a sensitivity to thinning distance applied for GNSS ZTD observations but not to modifications to the number of predictors used in the variational bias correction applied. In addition it is demonstrated that the assimilation of GNSS ZTD can benefit from more general data assimilation enhancements and that there is an interaction of GNSS ZTD with other types of observations used in the data assimilation. Future plans include further investigation of optimal thinning distances and application of more advanced data assimilation techniques.

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.

scholarly journals Evaluating the use of Aeolus satellite observations in the regional numerical weather prediction (NWP) model Harmonie–Arome

2021 ◽  
Vol 14 (9) ◽  
pp. 5925-5938
Author(s):  
Susanna Hagelin ◽  
Roohollah Azad ◽  
Magnus Lindskog ◽  
Harald Schyberg ◽  
Heiner Körnich
Keyword(s):  
Data Assimilation ◽  
Numerical Weather Prediction ◽  
Weather Prediction ◽  
Limited Area ◽  
Horizontal Line ◽  
Observation Error ◽  
Numerical Weather ◽  
Potential Improvement ◽  
Nwp Model ◽  
The Impact

Abstract. The impact of using wind observations from the Aeolus satellite in a limited-area numerical weather prediction (NWP) system is being investigated using the limited-area NWP model Harmonie–Arome over the Nordic region. We assimilate the horizontal line-of-sight (HLOS) winds observed by Aeolus using 3D-Var data assimilation for two different periods, one in September–October 2018 when the satellite was recently launched and a later period in April–May 2020 to investigate the updated data processing of the HLOS winds. We find that the quality of the Aeolus observations has degraded between the first and second experiment period over our domain. However, observations from Aeolus, in particular the Mie winds, have a clear impact on the analysis of the NWP model for both periods, whereas the forecast impact is neutral when compared against radiosondes. Results from evaluation of observation minus background and observation minus analysis departures based on Desroziers diagnostics show that the observation error should be increased for Aeolus data in our experiments, but the impact of doing so is small. We also see that there is potential improvement in using 4D-Var data assimilation, which generates flow-dependent analysis increments, with the Aeolus data.

scholarly journals On the Impact of Unmanned Aerial System Observations on Numerical Weather Prediction in the Coastal Zone

2018 ◽  
Vol 146 (2) ◽  
pp. 599-622 ◽  
Author(s):  
David D. Flagg ◽  
James D. Doyle ◽  
Teddy R. Holt ◽  
Daniel P. Tyndall ◽  
Clark M. Amerault ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Data Assimilation ◽  
Numerical Weather Prediction ◽  
Research Laboratory ◽  
Weather Prediction ◽  
Ocean Model ◽  
Naval Research ◽  
Unmanned Aerial System ◽  
Numerical Weather ◽  
The Impact

Abstract The Trident Warrior observational field campaign conducted off the U.S. mid-Atlantic coast in July 2013 included the deployment of an unmanned aerial system (UAS) with several payloads on board for atmospheric and oceanic observation. These UAS observations, spanning seven flights over 5 days in the lowest 1550 m above mean sea level, were assimilated into a three-dimensional variational data assimilation (DA) system [the Naval Research Laboratory Atmospheric Variational Data Assimilation System (NAVDAS)] used to generate analyses for a numerical weather prediction model [the Coupled Ocean–Atmosphere Mesoscale Prediction System (COAMPS)] with a coupled ocean model [the Naval Research Laboratory Navy Coastal Ocean Model (NCOM)]. The impact of the assimilated UAS observations on short-term atmospheric prediction performance is evaluated and quantified. Observations collected from 50 radiosonde launches during the campaign adjacent to the UAS flight paths serve as model forecast verification. Experiments reveal a substantial reduction of model bias in forecast temperature and moisture profiles consistently throughout the campaign period due to the assimilation of UAS observations. The model error reduction is most substantial in the vicinity of the inversion at the top of the model-estimated boundary layer. Investigations reveal a consistent improvement to prediction of the vertical position, strength, and depth of the boundary layer inversion. The relative impact of UAS observations is explored further with experiments of systematic denial of data streams from the NAVDAS DA system and removal of individual measurement sources on the UAS platform.

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 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.

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>

scholarly journals Impact of Radiosonde Balloon Drift on Numerical Weather Prediction and Verification

2013 ◽  
Vol 28 (3) ◽  
pp. 772-782 ◽  
Author(s):  
Stéphane Laroche ◽  
Réal Sarrazin
Keyword(s):  
Data Assimilation ◽  
Numerical Weather Prediction ◽  
Weather Prediction ◽  
Radiosonde Data ◽  
Horizontal Wind ◽  
Numerical Weather ◽  
Ascent Time ◽  
Verification Systems ◽  
The Impact ◽  
Range Forecasts

Abstract Radiosonde observations employed in real-time numerical weather prediction (NWP) applications are disseminated through the Global Telecommunication System (GTS) using alphanumeric codes. These codes do not include information about the position and elapsed ascent time of the balloon. Consequently, the horizontal balloon drift has generally been either ignored or estimated in data assimilation systems for NWP. With the increasing resolution of atmospheric models, it is now important to consider the positions and times of radiosonde data in both data assimilation and forecast verification systems. This information is now available in the Binary Universal Form for the Representation of Meteorological Data (BUFR) code for radiosonde data. This latter code will progressively replace the alphanumeric codes for all radiosonde data transmitted on the GTS. As a result, a strategy should be adopted by NWP centers to deal with the various codes for radiosonde data during this transition. In this work, a method for estimating the balloon drift position from reported horizontal wind components and a representative elapsed ascent time profile are developed and tested. This allows for estimating the missing positions and times information of radiosonde data in alphanumeric reports, and then for processing them like those available in BUFR code. The impact of neglecting the balloon position in data assimilation and verification systems is shown to be significant in short-range forecasts in the upper troposphere and stratosphere, especially for the zonal wind field in the Northern Hemisphere winter season. Medium-range forecasts are also improved overall when the horizontal position of radiosonde data is retrieved.

Sign in / Sign up

Export Citation Format

Share Document