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

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.

2014 ◽  
Vol 7 (3) ◽  
pp. 965-979 ◽  
Author(s):  
M. Diamantakis ◽  
J. Flemming

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.


Forecasting ◽  
2020 ◽  
Vol 2 (2) ◽  
pp. 130-150 ◽  
Author(s):  
João Perdigão ◽  
Paulo Canhoto ◽  
Rui Salgado ◽  
Maria João Costa

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.


2021 ◽  
Author(s):  
Vinícius Almeida ◽  
Gutemberg França ◽  
Francisco Albuquerque Neto ◽  
Haroldo Campos Velho ◽  
Manoel Almeida ◽  
...  

<p>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´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 São Paulo-Rio de Janeiro route. Finally, the steps in development and the futures are superficially covered.</p>


2014 ◽  
Vol 14 (5) ◽  
pp. 1059-1070 ◽  
Author(s):  
M. A. Picornell ◽  
J. Campins ◽  
A. Jansà

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.


Atmosphere ◽  
2018 ◽  
Vol 9 (12) ◽  
pp. 484 ◽  
Author(s):  
Ana Firanj Sremac ◽  
Branislava Lalić ◽  
Milena Marčić ◽  
Ljiljana Dekić

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.


2013 ◽  
Vol 341-342 ◽  
pp. 1303-1307 ◽  
Author(s):  
Jian Dong Mao ◽  
Xiao Jing Zhang ◽  
Juan Li

Accurate short-term wind power forecasting has important significance to safety, stability and economy of power system dispatching and also it is a difficult problem in practical engineering application. In this paper, by use of the data of numerical weather forecast, such as wind speed, wind direction, temperature, relative humidity and pressure of atmosphere, a short-term wind power forecasting system based on BP neural network has been developed. For verifying the feasibility of the system, some experiments have been were carried out. The results show that the system is capable of predicting accurately the wind power of future 24 hours and the forecasting accuracy of 85.6% is obtained. The work of this paper has important engineering directive significance to the similar wind power forecasting system.


2007 ◽  
Vol 7 (2) ◽  
pp. 5515-5552 ◽  
Author(s):  
C. Ren ◽  
A. R. MacKenzie ◽  
C. Schiller ◽  
G. Shur ◽  
V. Yushkov

Abstract. We have developed a Lagrangian air-parcel cirrus model (LACM), to diagnose the processes controlling water in the tropical tropopause layer (TTL). LACM applies parameterised microphysics to air parcel trajectories. The parameterisation includes the homogeneous freezing of aerosol droplets, the growth/sublimation of ice particles, and sedimentation of ice particles, so capturing the main dehydration mechanism for air in the TTL. Rehydration is also considered by resetting the water vapour mixing ratio in an air parcel to the value at the point in the 4-D analysis/forecast data used to generate the trajectories, but only when certain conditions, indicative of convection, are satisfied. These conditions are imposed to confine what processes contribute to rehydration. The conditions act to restrict rehydration of the Lagrangian air parcels to regions where convective transport of water vapour from below is significant, at least to the extent that the analysis/forecast captures this process. The inclusion of hydration and dehydration mechanisms in LACM results in total water fields near tropical convection that have more of the "stripey" character of satellite observations of high cloud, than do either the ECMWF analysis or trajectories without microphysics. The mixing ratios of total water in the TTL, measured by a high-altitude aircraft over Brazil (during the TROCCINOX campaign), have been reconstructed by LACM using trajectories generated from ECMWF analysis. Two other Lagrangian reconstructions are also tested: linear interpolation of ECMWF analysed specific humidity onto the aircraft flight track, and instantaneous dehydration to the saturation vapour pressure over ice along trajectories. The reconstructed total water mixing ratios along aircraft flight tracks are compared with observations from the FISH total water hygrometer. Process-oriented analysis shows that modelled cirrus cloud events are responsible for dehydrating the air parcels coming from lower levels, resulting in total water mixing ratios as low as 2 μmol/mol. Without adding water back to some of the trajectories, the LACM and instantaneous-dehydration reconstructions have a dry bias. The interpolated-ECMWF reconstruction does not suffer this dry bias, because convection in the ECMWF model moistens air parcels dramatically, by pumping moist air upwards. This indicates that the ECMWF model captures the gross features of the rehydration of air in the TTL by convection. Overall, the ECMWF models captures well the exponential decrease in total water mixing ratio with height above 250 hPa, so that all the reconstruction techniques capture more than 75% of the variance in the measured total water mixing ratios over the depth of the TTL. We have therefore developed a simple method for re-setting the total water in LACM using the ECMWF-analysed specific humidity in regions where the model predicts convection. By picking up the main contributing processes to dehydration and rehydration in the TTL, LACM reconstructs total water mixing ratios along aircraft flight tracks at the top of the TTL, close to the cold point, that are always in substantially better agreement with observations than instantaneous-dehydration reconstructions, and better than the ECMWF analysis for regions of high relative humidity and cloud.


Author(s):  
Peter Düben ◽  
Nils Wedi ◽  
Sami Saarinen ◽  
Christian Zeman

<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>


2021 ◽  
Author(s):  
Thomas Röösli ◽  
David N. Bresch

<p>Weather extremes can have high socio-economic impacts. Better impact forecasting and preventive action help to reduce these impacts. In Switzerland, the winter windstorms caused high building damage, felled trees and interrupted traffic and power. Events such as Burglind-Eleanor in January 2018 are a learning opportunity for weather warnings, risk modelling and decision-making.</p><p>We have developed and implemented an operational impact forecasting system for building damage due to wind events in Switzerland. We use the ensemble weather forecast of wind gusts produced by the national meteorological agency MeteoSwiss. We couple this hazard information with a spatially explicit impact model (CLIMADA) for building damages due to winter windstorms. Each day, the impact forecasting system publishes a probabilistic forecast of the expected building damages on a spatial grid.</p><p>This system produces promising results for major historical storms when compared to aggregated daily building insurance claims data from a public building insurer of the canton of Zurich. The daily impact forecasts were qualitatively categorized as (1) successful (2) miss or (3) false alarm. The impacts of windstorm Burglind-Eleanor and five other winter windstorms were forecasted reasonably well, with four successful forecasts, one miss and one false alarm.</p><p> The building damage due to smaller storm extremes was not as successfully forecasted. Thunderstorms are not as well forecasted with 2 days’ lead time and as a result the impact forecasting system produces more misses and false alarms outside the winter storm season. For the Alpine-specific southerly Foehn winds, the impact forecasts produce many false alarms, probably caused by an overestimation of wind gusts in the weather forecast.</p><p>The forecasting system can be used to improve weather warnings and allocate resources and staff in the claims handling process of building insurances. This will help to improve recovery time and costs to institutions and individuals. The open-source code and open meteorological data makes this implementation transferable to other hazard types and other geographical regions.</p>


2014 ◽  
Vol 7 (3) ◽  
pp. 909-929 ◽  
Author(s):  
J. Thuburn ◽  
C. J. Cotter ◽  
T. Dubos

Abstract. A new algorithm is presented for the solution of the shallow water equations on quasi-uniform spherical grids. It combines a mimetic finite volume spatial discretization with a Crank–Nicolson time discretization of fast waves and an accurate and conservative forward-in-time advection scheme for mass and potential vorticity (PV). The algorithm is implemented and tested on two families of grids: hexagonal–icosahedral Voronoi grids, and modified equiangular cubed-sphere grids. Results of a variety of tests are presented, including convergence of the discrete scalar Laplacian and Coriolis operators, advection, solid body rotation, flow over an isolated mountain, and a barotropically unstable jet. The results confirm a number of desirable properties for which the scheme was designed: exact mass conservation, very good available energy and potential enstrophy conservation, consistent mass, PV and tracer transport, and good preservation of balance including vanishing ∇ × ∇, steady geostrophic modes, and accurate PV advection. The scheme is stable for large wave Courant numbers and advective Courant numbers up to about 1. In the most idealized tests the overall accuracy of the scheme appears to be limited by the accuracy of the Coriolis and other mimetic spatial operators, particularly on the cubed-sphere grid. On the hexagonal grid there is no evidence for damaging effects of computational Rossby modes, despite attempts to force them explicitly.


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