scholarly journals Global mass fixer algorithms for conservative tracer transport in the ECMWF model

2014 ◽  
Vol 7 (3) ◽  
pp. 965-979 ◽  
Author(s):  
M. Diamantakis ◽  
J. Flemming
Keyword(s):  
Atmospheric Dispersion ◽  
Mass Conservation ◽  
Weather Forecast ◽  
Specific Humidity ◽  
Tracer Transport ◽  
Weather Forecasts ◽  
Forecasting System ◽  
Solution Accuracy ◽  
Atmospheric Tracers ◽  
Ecmwf Model

Abstract. Various mass fixer algorithms (MFAs) have been implemented in the Integrated Forecasting System (IFS) of the European Centre for Medium-Range Weather Forecasts (ECMWF) to ensure mass conservation of atmospheric tracers within the semi-Lagrangian (SL) advection scheme. Emphasis has been placed in implementing schemes that despite being primarily global in nature adjust the solution mostly in regions where the advected field has large gradients and therefore interpolation (transport) error is assumed larger. The MFAs have been tested in weather forecast, idealised and atmospheric dispersion cases. Applying these fixers to specific humidity and cloud fields did not change the accuracy of 10-day forecasts. In other words, global mass tracer conservation is achieved without deteriorating the solution accuracy. However, for longer forecast timescales or for forecasts in which correlated species are transported, experiments suggest that MFAs may improve IFS forecasts.

scholarly journals Global mass fixer algorithms for conservative tracer transport in the ECMWF model

2014 ◽  
Vol 7 (1) ◽  
pp. 777-814 ◽  
Author(s):  
M. Diamantakis ◽  
J. Flemming
Keyword(s):  
Atmospheric Dispersion ◽  
Mass Conservation ◽  
Weather Forecast ◽  
Specific Humidity ◽  
Tracer Transport ◽  
Conservative Tracer ◽  
Forecasting System ◽  
Solution Accuracy ◽  
Atmospheric Tracers ◽  
Ecmwf Model

Abstract. Various mass fixer algorithms (MFA) have been implemented in the Integrated Forecasting System (IFS) of ECMWF to ensure mass conservation of atmospheric tracers within the Semi-Lagrangian (SL) advection scheme. Emphasis has been placed in implementing schemes that despite being primarily global in nature adjust the solution mostly in regions where the advected field has large gradients and therefore interpolation (transport) error is assumed larger. The MFA have been tested in weather forecast, idealised and atmospheric dispersion cases. Applying these fixers to specific humidity and cloud fields did not change the accuracy of 10 day forecasts. In other words, global mass tracer conservation is achieved without deteriorating the solution accuracy. However, for longer forecast timescales or for forecasts in which correlated species are transported, experiments suggest that MFA may improve IFS forecasts.

scholarly journals Global simulations of the atmosphere at 1.45 km grid-spacing with the Integrated Forecasting System

2020 ◽  
Author(s):  
Peter Düben ◽  
Nils Wedi ◽  
Sami Saarinen ◽  
Christian Zeman
Keyword(s):  
Initial Conditions ◽  
Weather Forecast ◽  
Wave Model ◽  
Shallow Convection ◽  
Grid Spacing ◽  
Time Step ◽  
Weather Forecasts ◽  
Forecasting System ◽  
Diabatic Forcing ◽  
Physical Phenomena

<p>Global simulations with 1.45 km grid-spacing are presented that were performed with the Integrated Forecasting System (IFS) of the European Centre for Medium-Range Weather Forecasts (ECMWF). Simulations are uncoupled (without ocean, sea-ice or wave model), using 62 or 137 vertical levels and the full complexity of weather forecast simulations including recent date initial conditions, real-world topography, and state-of-the-art physical parametrizations and diabatic forcing including shallow convection, turbulent diffusion, radiation and five categories for the water substance (vapour, liquid, ice, rain, snow). Simulations are evaluated with regard to computational efficiency and model fidelity. Scaling results are presented that were performed on the fastest supercomputer in Europe - Piz Daint (Top 500, Nov 2018). Important choices for the model configuration at this unprecedented resolution for the IFS are discussed such as the use of hydrostatic and non-hydrostatic equations or the time resolution of physical phenomena which is defined by the length of the time step. </p><p>Our simulations indicate that the IFS model — based on spectral transforms with a semi-implicit, semi-Lagrangian time-stepping scheme in contrast to more local discretization techniques — can provide a meaningful baseline reference for O(1) km global simulations.</p>

scholarly journals Evaluation of Trade Cumulus in the ECMWF Model with Observations from CALIPSO

2010 ◽  
Vol 138 (8) ◽  
pp. 3071-3083 ◽  
Author(s):  
Maike Ahlgrimm ◽  
Martin Köhler
Keyword(s):  
Cloud Fraction ◽  
Shallow Convection ◽  
Cumulus Clouds ◽  
Weather Forecasts ◽  
Flux Parameterization ◽  
Forecasting System ◽  
Grid Points ◽  
Threshold Criteria ◽  
Ecmwf Model ◽  
Good Agreement

Abstract Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) are used to assess trade cumulus cloudiness in three versions of the Integrated Forecasting System of the European Centre for Medium-Range Weather Forecasts. The observations are recast onto the model grid, and two simple threshold criteria for cloud-top height and cloud fraction are used to identify grid points containing trade cumulus clouds. The cloud fraction and cloud-top height distributions of the sample populations are then compared. Results show that all versions of the model overestimate the frequency of occurrence of trade cumulus clouds but underestimate their cloud fraction when present. These effects partially compensate. Cloud-top heights are overestimated in model cycles using the modified Tiedtke parameterization for shallow convection, but are in very good agreement with observations when the dual mass flux parameterization is introduced.

scholarly journals Technical note: Lowermost-stratospheric moist bias in ECMWF IFS model diagnosed from airborne GLORIA observations during winter/spring 2016

2020 ◽  
Author(s):  
Wolfgang Woiwode ◽  
Andreas Dörnbrack ◽  
Inna Polichtchouk ◽  
Sören Johansson ◽  
Ben Harvey ◽  
...  
Keyword(s):  
Weather Forecast ◽  
Horizontal Resolution ◽  
Technical Note ◽  
Cold Bias ◽  
Air Masses ◽  
Weather Forecasts ◽  
Time Period ◽  
Forecasting System ◽  
Numerical Weather Forecast

Abstract. Numerical weather forecast systems like the ECMWF IFS (European Centre for Medium-Range Weather Forecasts – Integrated Forecasting System) are known to be affected by a moist bias in the extratropical lowermost stratosphere (LMS) which results in a systematic cold bias there. We use high spatial resolution water vapour measurements by the airborne 15 infrared limb-imager GLORIA (Gimballed Limb Observer for Radiance Imaging of the Atmosphere) during the PGS (POLSTRACC/GW-LCYLCE-II/SALSA) campaign to study the LMS moist bias in ECMWF analyses and 12 h forecasts in the season from January to March 2016. Thereby, we exploit the 2-dimensional observational capabilities of GLORIA, when compared to in situ observations, and the higher vertical and horizontal resolution, when compared to satellite observations. Using GLORIA observations taken during five flights in the polar sub-vortex region around Scandinavia and Greenland, we 20 diagnose a systematic moist bias in the LMS peaking at +50 % at potential vorticity levels of 6 to 10 PVU. In the diagnosed time period, the moist bias reduces at the highest and driest air masses observed, but clearly persists at lower levels until mid-March. Sensitivity experiments with more frequent temporal output, lower horizontal resolution, and higher/lower vertical resolution, show the short-term forecasts to be practically insensitive to these parameters on time scales of

scholarly journals Assessment of Direct Normal Irradiance Forecasts Based on IFS/ECMWF Data and Observations in the South of Portugal

Forecasting ◽  
2020 ◽  
Vol 2 (2) ◽  
pp. 130-150 ◽  
Author(s):  
João Perdigão ◽  
Paulo Canhoto ◽  
Rui Salgado ◽  
Maria João Costa
Keyword(s):  
Correlation Coefficients ◽  
Weather Forecast ◽  
The South ◽  
Medium Range Weather Forecast ◽  
Direct Normal Irradiance ◽  
Daily Data ◽  
Forecasting System ◽  
Forecast Time ◽  
Sky Conditions ◽  
Ecmwf Model

Direct Normal Irradiance (DNI) predictions obtained from the Integrated Forecasting System of the European Centre for Medium-Range Weather Forecast (IFS/ECMWF) were compared against ground-based observational data for one location at the south of Portugal (Évora). Hourly and daily DNI values were analyzed for different temporal forecast horizons (1 to 3 days ahead) and results show that the IFS/ECMWF slightly overestimates DNI for the period of analysis (1 August 2018 until 31 July 2019) with a fairly good agreement between model and observations. Hourly basis evaluation shows relatively high errors, independently of the forecast day. Root mean square error increases as the forecast time increases with a relative error of ~45% between the first and the last forecast. Similar patterns are observed in the daily analysis with comparable magnitude errors. The correlation coefficients between forecast and observed data are above 0.7 for both hourly and daily data. A methodology based on a new DNI attenuation Index (DAI) was developed to estimate cloud fraction from hourly values integrated over a day and, with that, to correlate the accuracy of the forecast with sky conditions. This correlation with DAI reveals that in IFS/ECMWF model, the atmosphere as being more transparent than reality since cloud cover is underestimated in the majority of the months of the year, taking the ground-based measurements as a reference. The use of the DAI estimator confirms that the errors in IFS/ECMWF are larger under cloudy skies than under clear sky. The development and application of a post-processing methodology improves the DNI predictions from the IFS/ECMWF outputs, with a decrease of error of the order of ~30%, when compared with raw data.

scholarly journals Characterising extratropical near tropopause analysis humidity biases and their radiative effects on temperature forecasts

2021 ◽  
Author(s):  
Jake Bland ◽  
Suzanne Gray ◽  
John Methven ◽  
Richard Forbes
Keyword(s):  
Prediction Models ◽  
Initial Conditions ◽  
Weather Prediction ◽  
Specific Humidity ◽  
Cold Bias ◽  
Radiative Effects ◽  
Weather Forecasts ◽  
Forecast Models ◽  
Forecasting System ◽  
Temperature Errors

<p>A cold bias in the extratropical lowermost stratosphere in forecasts is one of the most prominent systematic temperature errors in numerical weather prediction models. Hypothesized causes of this bias include radiative effects from a collocated moist bias in model analyses. Such biases would be expected to affect extratropical dynamics and result in the misrepresentation of wave propagation at tropopause level. Here the extent to which these biases are connected is quantified. Observations from radiosondes are compared to operational analyses and forecasts from the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecasting System (IFS) and Met Office Unified Model (MetUM) to determine the magnitude and vertical structure of these biases. Both operational models over-estimate lowermost stratospheric specific humidity by around 70% of the observed values on average, around 1km above the tropopause. This moist bias is already present in the initial conditions and changes little in forecasts over the first five days. Though temperatures are represented well in the analyses, the IFS forecasts anomalously cool in the lower stratosphere, relative to verifying radiosonde observations, by 0.2K per day. The IFS single column model is used to show this temperature change can be attributed to increased long-wave radiative cooling due to the lowermost stratospheric moist bias in the initial conditions. However, the MetUM temperature biases cannot be entirely attributed to the moist bias, and another significant factor must be present. These results highlight the importance of improving the humidity analysis to reduce the extratropical lowermost stratospheric cold bias in forecast models and the need to understand and mitigate the causes of the moist bias in these models.</p>

scholarly journals Technical note: Lowermost-stratosphere moist bias in ECMWF IFS model diagnosed from airborne GLORIA observations during winter–spring 2016

2020 ◽  
Vol 20 (23) ◽  
pp. 15379-15387
Author(s):  
Wolfgang Woiwode ◽  
Andreas Dörnbrack ◽  
Inna Polichtchouk ◽  
Sören Johansson ◽  
Ben Harvey ◽  
...  
Keyword(s):  
Water Vapor ◽  
Initial Conditions ◽  
Weather Forecast ◽  
Horizontal Resolution ◽  
Technical Note ◽  
Cold Bias ◽  
Weather Forecasts ◽  
Time Period ◽  
Forecasting System ◽  
Numerical Weather Forecast

Abstract. Numerical weather forecast systems like the ECMWF IFS (European Centre for Medium-Range Weather Forecasts – Integrated Forecasting System) are known to be affected by a moist bias in the extratropical lowermost stratosphere (LMS) which results in a systematic cold bias there. We use high-spatial-resolution water vapor measurements by the airborne infrared limb-imager GLORIA (Gimballed Limb Observer for Radiance Imaging of the Atmosphere) during the PGS (POLSTRACC/GW-LCYCLE-II/SALSA) campaign to study the LMS moist bias in ECMWF analyses and 12 h forecasts from January to March 2016. Thereby, we exploit the two-dimensional observational capabilities of GLORIA, when compared to in situ observations, and the higher vertical and horizontal resolution, when compared to satellite observations. Using GLORIA observations taken during five flights in the polar sub-vortex region around Scandinavia and Greenland, we diagnose a systematic moist bias in the LMS exceeding +50 % (January) to +30 % (March) at potential vorticity levels from 10 PVU (∼ highest level accessed with suitable coverage) to 7 PVU. In the diagnosed time period, the moist bias decreases at the highest and driest air masses observed but clearly persists at lower levels until mid-March. Sensitivity experiments with more frequent temporal output, and lower or higher horizontal and vertical resolution, show the short-term forecasts to be practically insensitive to these parameters on timescales of < 12 h. Our results confirm that the diagnosed moist bias is already present in the initial conditions (i.e., the analysis) and thus support the hypothesis that the cold bias develops as a result of forecast initialization. The moist bias in the analysis might be explained by a model bias together with the lack of water vapor observations suitable for assimilation above the tropopause.

Brazilian aviation nowcasting system: current stage and some results

2021 ◽  
Author(s):  
Vinícius Almeida ◽  
Gutemberg França ◽  
Francisco Albuquerque Neto ◽  
Haroldo Campos Velho ◽  
Manoel Almeida ◽  
...  
Keyword(s):  
Rio De Janeiro ◽  
Remote Sensing Data ◽  
Weather Forecast ◽  
Weather Data ◽  
Vertical Acceleration ◽  
In Situ Data ◽  
Forecasting System ◽  
Under Construction ◽  
Convective Weather

&lt;p&gt;Emphasizes some aspects of the aviation forecasting system under construction for use by the integrated meteorological center (CIMAER) in Brazil. It consists of a set of hybrid models based on determinism and machine learning that use remote sensing data (such as lighting sensor, SODAR, satellite and soon RADAR), in situ data (from the surface weather station and radiosonde) and aircraft data (such as retransmission of aircraft weather data and vertical acceleration). The idea is to gradually operationalize the system to assist CIMAER&amp;#180;s meteorologists in generating their nowcasting, for example, of visibility, ceiling, turbulence, convective weather, ice, etc. with objectivity and precision. Some test results of the developed nowcasting models are highlighted as examples of nowcasting namely: a) visibility and ceiling up to 1h for Santos Dumont airport; b) 6-8h convective weather forecast for the Rio de Janeiro area and the S&amp;#227;o Paulo-Rio de Janeiro route. Finally, the steps in development and the futures are superficially covered.&lt;/p&gt;

scholarly journals Detection and thermal description of medicanes from numerical simulation

2014 ◽  
Vol 14 (5) ◽  
pp. 1059-1070 ◽  
Author(s):  
M. A. Picornell ◽  
J. Campins ◽  
A. Jansà
Keyword(s):  
Numerical Simulation ◽  
Thermal Structure ◽  
Weather Prediction ◽  
Weather Forecast ◽  
Small Scale ◽  
Medium Range Weather Forecast ◽  
Warm Core ◽  
Strong Winds ◽  
Nwp Model ◽  
Ecmwf Model

Abstract. Tropical-like cyclones rarely affect the Mediterranean region but they can produce strong winds and heavy precipitations. These warm-core cyclones, called MEDICANES (MEDIterranean hurriCANES), are small in size, develop over the sea and are infrequent. For these reasons, the detection and forecast of medicanes are a difficult task and many efforts have been devoted to identify them. The goals of this work are to contribute to a proper description of these structures and to develop some criteria to identify medicanes from numerical weather prediction (NWP) model outputs. To do that, existing methodologies for detecting, characterizating and tracking cyclones have been adapted to small-scale intense cyclonic perturbations. First, a mesocyclone detection and tracking algorithm has been modified to select intense cyclones. Next, the parameters that define the Hart's cyclone phase diagram are tuned and calculated to examine their thermal structure. Four well-known medicane events have been described from numerical simulation outputs of the European Centre for Medium-Range Weather Forecast (ECMWF) model. The predicted cyclones and their evolution have been validated against available observational data and numerical analyses from the literature.

scholarly journals Toward a Weather-Based Forecasting System for Fire Blight and Downy Mildew

Atmosphere ◽  
2018 ◽  
Vol 9 (12) ◽  
pp. 484 ◽  
Author(s):  
Ana Firanj Sremac ◽  
Branislava Lalić ◽  
Milena Marčić ◽  
Ljiljana Dekić
Keyword(s):  
Downy Mildew ◽  
Fire Blight ◽  
Meteorological Data ◽  
Weather Prediction ◽  
Weather Forecast ◽  
Atmospheric Model ◽  
Plasmopara Viticola ◽  
Forecasting System ◽  
Nwp Model ◽  
The Impact

The aim of this research is to present a weather-based forecasting system for apple fire blight (Erwinia amylovora) and downy mildew of grapevine (Plasmopara viticola) under Serbian agroecological conditions and test its efficacy. The weather-based forecasting system contains Numerical Weather Prediction (NWP) model outputs and a disease occurrence model. The weather forecast used is a product of the high-resolution forecast (HRES) atmospheric model by the European Centre for Medium-Range Weather Forecasts (ECMWF). For disease modelling, we selected a biometeorological system for messages on the occurrence of diseases in fruits and vines (BAHUS) because it contains both diseases with well-known and tested algorithms. Several comparisons were made: (1) forecasted variables for the fifth day are compared against measurements from the agrometeorological network at seven locations for three months (March, April, and May) in the period 2012–2018 to determine forecast efficacy; (2) BAHUS runs driven with observed and forecast meteorology were compared to test the impact of forecasted meteorological data; and (3) BAHUS runs were compared with field disease observations to estimate system efficacy in plant disease forecasts. The BAHUS runs with forecasted and observed meteorology were in good agreement. The results obtained encourage further development, with the goal of fully utilizing this weather-based forecasting system.

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