scholarly journals The impact of Aeolus wind retrievals in ECMWF global weather forecasts

2021 ◽  
Author(s):  
Michael P. Rennie ◽  
Lars Isaksen ◽  
Fabian Weiler ◽  
Jos Kloe ◽  
Thomas Kanitz ◽  
...  
Keyword(s):  
Weather Forecasts ◽  
Wind Retrievals ◽  
The Impact

scholarly journals Inclusion of biomass burning in WRF-Chem: impact of wildfires on weather forecasts

2011 ◽  
Vol 11 (11) ◽  
pp. 5289-5303 ◽  
Author(s):  
G. Grell ◽  
S. R. Freitas ◽  
M. Stuefer ◽  
J. Fast
Keyword(s):  
Biomass Burning ◽  
Cloud Model ◽  
Cloud Condensation Nuclei ◽  
Cloud Microphysics ◽  
Fire Season ◽  
Strong Impact ◽  
Emission Rates ◽  
Weather Forecasts ◽  
High Concentrations ◽  
The Impact

Abstract. A plume rise algorithm for wildfires was included in WRF-Chem, and applied to look at the impact of intense wildfires during the 2004 Alaska wildfire season on weather simulations using model resolutions of 10 km and 2 km. Biomass burning emissions were estimated using a biomass burning emissions model. In addition, a 1-D, time-dependent cloud model was used online in WRF-Chem to estimate injection heights as well as the vertical distribution of the emission rates. It was shown that with the inclusion of the intense wildfires of the 2004 fire season in the model simulations, the interaction of the aerosols with the atmospheric radiation led to significant modifications of vertical profiles of temperature and moisture in cloud-free areas. On the other hand, when clouds were present, the high concentrations of fine aerosol (PM2.5) and the resulting large numbers of Cloud Condensation Nuclei (CCN) had a strong impact on clouds and cloud microphysics, with decreased precipitation coverage and precipitation amounts during the first 12 h of the integration. During the afternoon, storms were of convective nature and appeared significantly stronger, probably as a result of both the interaction of aerosols with radiation (through an increase in CAPE) as well as the interaction with cloud microphysics.

scholarly journals The Impact of Imperfect Weather Forecasts on Wind Power Forecasting Performance: Evidence from Two Wind Farms in Greece

Energies ◽  
2020 ◽  
Vol 13 (8) ◽  
pp. 1880 ◽  
Author(s):  
Evangelos Spiliotis ◽  
Fotios Petropoulos ◽  
Konstantinos Nikolopoulos
Keyword(s):  
Power Generation ◽  
Wind Power ◽  
Renewable Energy Sources ◽  
Stress Test ◽  
Wind Farms ◽  
Weather Variables ◽  
Test Analysis ◽  
Weather Forecasts ◽  
Forecasting Performance ◽  
The Impact

Weather variables are an important driver of power generation from renewable energy sources. However, accurately predicting such variables is a challenging task, which has a significant impact on the accuracy of the power generation forecasts. In this study, we explore the impact of imperfect weather forecasts on two classes of forecasting methods (statistical and machine learning) for the case of wind power generation. We perform a stress test analysis to measure the robustness of different methods on the imperfect weather input, focusing on both the point forecasts and the 95% prediction intervals. The results indicate that different methods should be considered according to the uncertainty characterizing the weather forecasts.

scholarly journals The Madden–Julian Oscillation and Boreal Winter Forecast Skill: An Analysis of NCEP CFSv2 Reforecasts

2015 ◽  
Vol 28 (15) ◽  
pp. 6297-6307 ◽  
Author(s):  
Charles Jones ◽  
Abheera Hazra ◽  
Leila M. V. Carvalho
Keyword(s):  
Forecast Skill ◽  
Western Pacific ◽  
Boreal Winter ◽  
Lead Times ◽  
Madden Julian Oscillation ◽  
Main Mode ◽  
Weather Forecasts ◽  
Synoptic Variability ◽  
The Impact ◽  
The Western Pacific

Abstract The Madden–Julian oscillation (MJO) is the main mode of tropical intraseasonal variations and bridges weather and climate. Because the MJO has a slow eastward propagation and longer time scale relative to synoptic variability, significant interest exists in exploring the predictability of the MJO and its influence on extended-range weather forecasts (i.e., 2–4-week lead times). This study investigates the impact of the MJO on the forecast skill in Northern Hemisphere extratropics during boreal winter. Several 45-day forecasts of geopotential height (500 hPa) from NCEP Climate Forecast System version 2 (CFSv2) reforecasts are used (1 November–31 March 1999–2010). The variability of the MJO expressed as different amplitudes, durations, and recurrence (i.e., primary and successive events) and their influence on forecast skill is analyzed and compared against inactive periods (i.e., null cases). In general, forecast skill during enhanced MJO convection over the western Pacific is systematically higher than in inactive days. When the enhanced MJO convection is over the Maritime Continent, forecasts are lower than in null cases, suggesting potential model deficiencies in accurately forecasting the eastward propagation of the MJO over that region and the associated extratropical response. In contrast, forecasts are more skillful than null cases when the enhanced convection is over the western Pacific and during long, intense, and successive MJO events. These results underscore the importance of the MJO as a potential source of predictability on 2–4-week lead times.

The Impact of Initial Condition and Warm Conveyor Belt Forecast Uncertainty on Variability in the Downstream Waveguide in an ECWMF Case Study

2019 ◽  
Vol 147 (11) ◽  
pp. 4071-4089 ◽  
Author(s):  
Jeremy D. Berman ◽  
Ryan D. Torn
Keyword(s):  
Conveyor Belt ◽  
Forecast Uncertainty ◽  
Ensemble Forecasts ◽  
Rossby Wave Breaking ◽  
Weather Forecasts ◽  
The North ◽  
Weather Events ◽  
High Impact Weather ◽  
Sensitivity Method ◽  
The Impact

Abstract Perturbations to the potential vorticity (PV) waveguide, which can result from latent heat release within the warm conveyor belt (WCB) of midlatitude cyclones, can lead to the downstream radiation of Rossby waves, and in turn high-impact weather events. Previous studies have hypothesized that forecast uncertainty associated with diabatic heating in WCBs can result in large downstream forecast variability; however, these studies have not established a direct connection between the two. This study evaluates the potential impact of latent heating variability in the WCB on subsequent downstream forecasts by applying the ensemble-based sensitivity method to European Centre for Medium-Range Weather Forecasts (ECMWF) ensemble forecasts of a cyclogenesis event over the North Atlantic. For this case, ensemble members with a more amplified ridge are associated with greater negative PV advection by the irrotational wind, which is associated with stronger lower-tropospheric southerly moisture transport east of the upstream cyclone in the WCB. This transport is sensitive to the pressure trough to the south of the cyclone along the cold front, which in turn is modulated by earlier differences in the motion of the air masses on either side of the front. The position of the cold air behind the front is modulated by upstream tropopause-based PV anomalies, such that a deeper pressure trough is associated with a more progressive flow pattern, originating from Rossby wave breaking over the North Pacific. Overall, these results suggest that more accurate forecasts of upstream PV anomalies and WCBs may reduce forecast uncertainty in the downstream waveguide.

scholarly journals Three-dimensional visualization of ensemble weather forecasts – Part 1: The visualization tool Met.3D (version 1.0)

2015 ◽  
Vol 8 (7) ◽  
pp. 2329-2353 ◽  
Author(s):  
M. Rautenhaus ◽  
M. Kern ◽  
A. Schäfler ◽  
R. Westermann
Keyword(s):  
Visual Analysis ◽  
Weather Forecasting ◽  
Spatial Perception ◽  
Three Dimensional ◽  
Atmospheric Model ◽  
Weather Forecasts ◽  
Research And Teaching ◽  
Grid Topology ◽  
Ensemble Visualization ◽  
The Impact

Abstract. We present "Met.3D", a new open-source tool for the interactive three-dimensional (3-D) visualization of numerical ensemble weather predictions. The tool has been developed to support weather forecasting during aircraft-based atmospheric field campaigns; however, it is applicable to further forecasting, research and teaching activities. Our work approaches challenging topics related to the visual analysis of numerical atmospheric model output – 3-D visualization, ensemble visualization and how both can be used in a meaningful way suited to weather forecasting. Met.3D builds a bridge from proven 2-D visualization methods commonly used in meteorology to 3-D visualization by combining both visualization types in a 3-D context. We address the issue of spatial perception in the 3-D view and present approaches to using the ensemble to allow the user to assess forecast uncertainty. Interactivity is key to our approach. Met.3D uses modern graphics technology to achieve interactive visualization on standard consumer hardware. The tool supports forecast data from the European Centre for Medium Range Weather Forecasts (ECMWF) and can operate directly on ECMWF hybrid sigma-pressure level grids. We describe the employed visualization algorithms, and analyse the impact of the ECMWF grid topology on computing 3-D ensemble statistical quantities. Our techniques are demonstrated with examples from the T-NAWDEX-Falcon 2012 (THORPEX – North Atlantic Waveguide and Downstream Impact Experiment) campaign.

scholarly journals SINGV – the Convective-Scale Numerical Weather Prediction System for Singapore

2019 ◽  
Vol 36 (3) ◽  
Author(s):  
Xiang-Yu Huang ◽  
Dale Barker ◽  
Stuart Webster ◽  
Anurag Dipankar ◽  
Adrian Lock ◽  
...  
Keyword(s):  
Numerical Weather Prediction ◽  
Weather Prediction ◽  
Extreme Rainfall ◽  
Prediction System ◽  
Local Data ◽  
Weather Forecasts ◽  
Numerical Weather ◽  
The United Kingdom ◽  
Convective Scale ◽  
The Impact

Extreme rainfall is one of the primary meteorological hazards in Singapore, as well as elsewhere in the deep tropics, and it can lead to significant local flooding. Since 2013, the Meteorological Service Singapore (MSS) and the United Kingdom Met Office (UKMO) have been collaborating to develop a convective-scale Numerical Weather Prediction (NWP) system, called SINGV. Its primary aim is to provide improved weather forecasts for Singapore and the surrounding region, with a focus on improved short-range prediction of localized heavy rainfall. This paper provides an overview of the SINGV development, the latest NWP capabilities at MSS and some key results of evaluation. The paper describes science advances relevant to the development of any km-scale NWP suitable for the deep tropics and provides some insights into the impact of local data assimilation and utility of ensemble predictions.

scholarly journals Impact of the sea surface temperature forcing on hindcasts of Madden-Julian Oscillation events using the ECMWF model

2012 ◽  
Vol 9 (4) ◽  
pp. 2535-2559
Author(s):  
E. de Boisséson ◽  
M. A. Balmaseda ◽  
F. Vitart ◽  
K. Mogensen
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Phase Relationship ◽  
Sea Surface ◽  
Madden Julian Oscillation ◽  
Weather Forecasts ◽  
Skill Scores ◽  
The Mean ◽  
Ecmwf Model ◽  
The Impact

Abstract. This paper explores the sensitivity of the prediction of Madden Julian Oscillation (MJO) events to different aspects of the sea surface temperature (SST) in the European Centre for Medium-range Weather Forecasts (ECMWF) model. The impact of temporal resolution of SST on the MJO is first evaluated via a set of monthly hindcast experiments. The experiments are conducted with an atmosphere forced by persisted SST anomalies, monthly and weekly SSTs. Skill scores are clearly degraded when weekly SSTs are replaced by monthly values or persisted anomalies. The new high resolution OSTIA SST daily reanalysis would in principle allow to establish the impact of daily versus weekly SST values on the MJO prediction. It is found however that OSTIA SSTs provide lower skill scores than the weekly product. Further experiments show that this loss of skill cannot be attributed to either the mean state or the daily frequency of OSTIA SSTs. Additional diagnostics show that the phase relationship between OSTIA SSTs and tropical convection is not optimal with repspect to observations. Such result suggests that capturing the correct SST-convection phase relationship is a major challenge for the MJO predictions.

scholarly journals Choices in the Verification of S2S Forecasts and Their Implications for Climate Services

2020 ◽  
Vol 148 (10) ◽  
pp. 3995-4008
Author(s):  
Andrea Manrique-Suñén ◽  
Nube Gonzalez-Reviriego ◽  
Verónica Torralba ◽  
Nicola Cortesi ◽  
Francisco J. Doblas-Reyes
Keyword(s):  
Skill Score ◽  
Climate Services ◽  
Near Surface ◽  
Weather Forecasts ◽  
Probabilistic Evaluation ◽  
Skill Scores ◽  
Medium Range ◽  
The Impact ◽  
Start Dates

AbstractSubseasonal predictions bridge the gap between medium-range weather forecasts and seasonal climate predictions. This time scale is crucial for operations and planning in many sectors such as energy and agriculture. For users to trust these predictions and efficiently make use of them in decision-making, the quality of predicted near-surface parameters needs to be systematically assessed. However, the method to follow in a probabilistic evaluation of subseasonal predictions is not trivial. This study aims to offer an illustration of the impact that the verification setup might have on the calculation of the skill scores, thus providing some guidelines for subseasonal forecast evaluation. For this, several forecast verification setups to calculate the fair ranked probability skill score for tercile categories have been designed. These setups use different number of samples to compute the fair RPSS as well as different ways to define the climatology, characterized by different time periods to average (week or month). These setups have been tested by evaluating 2-m temperature in ECMWF-Ext-ENS 20-yr hindcasts for all of the initializations in 2016 against the ERA-Interim reanalysis. Then, the implications on skill score values of each of the setups are analyzed. Results show that to obtain a robust skill score several start dates need to be employed. It is also shown that a constant monthly climatology over each calendar month may introduce spurious skill score associated with the seasonal cycle. A weekly climatology bears similar results to a monthly running-window climatology; however, the latter provides a better reference climatology when bias adjustment is applied.

scholarly journals Revisiting the synoptic-scale predictability of severe European winter storms using ECMWF ensemble reforecasts

2017 ◽  
Author(s):  
Florian Pantillon ◽  
Peter Knippertz ◽  
Ulrich Corsmeier
Keyword(s):  
Severity Index ◽  
Lead Times ◽  
Synoptic Scale ◽  
Winter Storms ◽  
Large Variability ◽  
Weather Forecasts ◽  
Wind Gusts ◽  
Extreme Wind ◽  
The Impact ◽  
Homogeneous Ensemble

Abstract. New insights into the synoptic-scale predictability of 25 severe European winter storms of the 1995–2015 period are obtained using the homogeneous ensemble reforecast dataset from the European Centre for Medium-Range Weather Forecasts. The predictability of the storms is assessed with different metrics including the track and intensity to investigate the storms’ dynamics and the Storm Severity Index to estimate the impact of the associated wind gusts. The storms are correctly predicted by the ensemble reforecasts up to 2–4 days ahead only, which restricts the use of ensemble average and spread to short lead times. At longer lead times, the Extreme Forecast Index and Shift of Tails are computed from the deviation of the ensemble reforecasts from the model climate. Based on these indices, the model has some skill in forecasting the area covered by extreme wind gusts up to 10 days, which indicates clear potential for the early warning of storms. However, a large variability is found between the predictability of individual storms and does not appear to be related to the storms’ characteristics. This may be due to the limited sample of 25 cases, but also suggests that each severe storm has its own dynamics and sources of forecast uncertainty.

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