Winter Subseasonal Wind Speed Forecasts for Finland from ECMWF

Abstract. The subseasonal forecasts from the ECMWF (European Centre for Medium-Range Weather Forecasts) were used to construct weekly mean wind speed forecasts for the spatially aggregated area in Finland. Reforecasts for the winters (November, December and January) of 2016–2017 and 2017–2018 were analysed. The ERA-Interim reanalysis was used as observations and climatological forecasts. We evaluated two types of forecasts, the deterministic forecasts and the probabilistic forecasts. Non-homogeneous Gaussian regression was used to bias-adjust both types of forecasts. The forecasts proved to be skilful until the third week, but the longest skilful lead time depends on the reference data sets and the verification scores used.

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Verification of the European subseasonal forecasts of wind speed and temperature

10.5194/egusphere-egu21-14728 ◽

2021 ◽

Author(s):

Naveen Goutham ◽

Riwal Plougonven ◽

Hiba Omrani ◽

Sylvie Parey ◽

Peter Tankov ◽

...

Keyword(s):

Wind Speed ◽

Value Chain ◽

Western Europe ◽

Grid Point ◽

Weather Forecasts ◽

Anomaly Correlation Coefficient ◽

Extended Range ◽

Medium Range ◽

Different Seasons ◽

Mean Wind Speed

The skill of predicted wind speed at 100 m and temperature at 2 m has been assessed in extended-range forecasts and hindcasts of the European Center for Medium-Range Weather Forecasts, starting from December 2015 to November 2019. The assessment was carried out over Europe grid-point wise and also by considering several spatially averaged country-sized domains, using standard scores such as the Continuous Ranked Probability Score and Anomaly Correlation Coefficient. The (re-)forecasts showed skill over climatology in predicting weekly mean wind speed and temperature well beyond two weeks. Even at a lead time of 6 weeks, the probability of the (re-)forecasts being skillful is greater than 50%, encouraging the use of operational subseasonal forecasts in the decision making value chain. The analysis also exhibited&#8203; significant differences in skill in the predictability of different variables, with temperature being more skillful than wind speed, and for different seasons, with winter allowing more skillful forecasts. The predictability also displayed a clear spatial pattern with forecasts for temperature having more skill for Eastern than for Western Europe, and wind speed forecasts having more skill in Northern than Southern Europe.

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Seasonal effects in the long-term correction of short-term wind measurements using reanalysis data

Wind Energy Science ◽

10.5194/wes-6-1473-2021 ◽

2021 ◽

Vol 6 (6) ◽

pp. 1473-1490

Author(s):

Alexander Basse ◽

Doron Callies ◽

Anselm Grötzner ◽

Lukas Pauscher

Keyword(s):

Wind Speed ◽

Reference Data ◽

Measurement Data ◽

Theoretical Framework ◽

Reanalysis Data ◽

Seasonal Effects ◽

Data Sets ◽

Mean Wind Speed ◽

Wind Measurements

Abstract. Measure–correlate–predict (MCP) approaches are often used to correct wind measurements to the long-term wind conditions on-site. This paper investigates systematic errors in MCP-based long-term corrections which occur if the measurement on-site covers only a few months (seasonal biases). In this context, two common linear MCP methods are tested and compared with regard to accuracy in mean, variance, and turbine energy production – namely, variance ratio (VR) and linear regression with residuals (LR). Wind measurement data from 18 sites with different terrain complexity in Germany are used (measurement heights between 100 and 140 m). Six different reanalysis data sets serve as the reference (long-term) wind data in the MCP calculations. All these reanalysis data sets showed an overpronounced annual course of wind speed (i.e., wind speeds too high in winter and too low in summer). However, despite the mathematical similarity of the two MCP methods, these errors in the data resulted in very different seasonal biases when either the VR or LR methods were used for the MCP calculations. In general, the VR method produced overestimations of the mean wind speed when measuring in summer and underestimations in the case of winter measurements. The LR method, in contrast, predominantly led to opposite results. An analysis of the bias in variance did not show such a clear seasonal variation. Overall, the variance error plays only a minor role for the accuracy in energy compared to the error in mean wind speed. Besides the experimental analysis, a theoretical framework is presented which explains these phenomena. This framework enables us to trace the seasonal biases to the mechanics of the methods and the properties of the reanalysis data sets. In summary, three aspects are identified as the main influential factors for the seasonal biases in mean wind speed: (1) the (dis-)similarity of the real wind conditions on-site in correlation and correction period (representativeness of the measurement period), (2) the capability of the reference data to reproduce the seasonal course of wind speed, and (3) the regression parameter β1 (slope) of the linear MCP method. This theoretical framework can also be considered valid for different measurement durations, other reference data sets, and other regions of the world.

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Impact of planetary waves on infrasound propagation uncertainties

10.5194/egusphere-egu21-15038 ◽

2021 ◽

Author(s):

Elisabeth Blanc ◽

Patrick Hupe ◽

Bernd Kaifler ◽

Natalie Kaifler ◽

Alexis Le Pichon ◽

...

Keyword(s):

Wave Activity ◽

Atmospheric Dynamics ◽

Planetary Waves ◽

Data Sets ◽

Atmospheric Models ◽

Period Range ◽

Weather Forecasts ◽

Atmospheric Disturbances ◽

Medium Range ◽

Model Improvement

The uncertainties in the infrasound technology arise from the middle atmospheric disturbances, which are partly underrepresented in the atmospheric models such as in the European Centre for Medium-Range Weather Forecasts (ECMWF) products used for infrasound propagation simulations. In the framework of the ARISE (Atmospheric dynamics Research InfraStructure in Europe) project, multi-instrument observations are performed to provide new data sets for model improvement and future assimilations. In an unexpected way, new observations using the autonomous CORAL lidar showed significant differences between ECMWF analysis fields and observations in Argentina in the period range between 0.1 and 10 days. The model underestimates the wave activity, especially in the summer. During the same season, the infrasound bulletins of the IS02 station in Argentina indicate the presence of two prevailing directions of the detections, which are not reflected by the simulations. Observations at the Haute Provence Observatory (OHP) are used for comparison in different geophysical conditions. The origin of the observed anomalies are discussed in term of planetary waves effect on the infrasound propagation.

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Verification of Ensemble-Based Uncertainty Circles around Tropical Cyclone Track Forecasts

Weather and Forecasting ◽

10.1175/waf-d-11-00007.1 ◽

2011 ◽

Vol 26 (5) ◽

pp. 664-676 ◽

Cited By ~ 21

Author(s):

Thierry Dupont ◽

Matthieu Plu ◽

Philippe Caroff ◽

Ghislain Faure

Keyword(s):

Tropical Cyclone ◽

Large Error ◽

Ensemble Prediction ◽

Probabilistic Forecasting ◽

Cyclone Track ◽

Ensemble Prediction System ◽

Weather Forecasts ◽

Probabilistic Forecasts ◽

Medium Range ◽

Uncertainty Information

Abstract Several tropical cyclone forecasting centers issue uncertainty information with regard to their official track forecasts, generally using the climatological distribution of position error. However, such methods are not able to convey information that depends on the situation. The purpose of the present study is to assess the skill of the Ensemble Prediction System (EPS) from the European Centre for Medium-Range Weather Forecasts (ECMWF) at measuring the uncertainty of up to 3-day track forecasts issued by the Regional Specialized Meteorological Centre (RSMC) La Réunion in the southwestern Indian Ocean. The dispersion of cyclone positions in the EPS is extracted and translated at the RSMC forecast position. The verification relies on existing methods for probabilistic forecasts that are presently adapted to a cyclone-position metric. First, the probability distribution of forecast positions is compared to the climatological distribution using Brier scores. The probabilistic forecasts have better scores than the climatology, particularly after applying a simple calibration scheme. Second, uncertainty circles are built by fixing the probability at 75%. Their skill at detecting small and large error values is assessed. The circles have some skill for large errors up to the 3-day forecast (and maybe after); but the detection of small radii is skillful only up to 2-day forecasts. The applied methodology may be used to assess and to compare the skill of different probabilistic forecasting systems of cyclone position.

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Predictability of a Mediterranean Tropical-Like Storm Downstream of the Extratropical Transition of Hurricane Helene (2006)

Monthly Weather Review ◽

10.1175/mwr-d-12-00164.1 ◽

2013 ◽

Vol 141 (6) ◽

pp. 1943-1962 ◽

Cited By ~ 13

Author(s):

Florian P. Pantillon ◽

Jean-Pierre Chaboureau ◽

Patrick J. Mascart ◽

Christine Lac

Keyword(s):

Tropical Cyclone ◽

Lead Time ◽

Large Scale ◽

Synoptic Situation ◽

British Isles ◽

Extratropical Transition ◽

Ensemble Forecasts ◽

Weather Forecasts ◽

Warm Core ◽

Medium Range

Abstract The extratropical transition (ET) of a tropical cyclone is known as a source of forecast uncertainty that can propagate far downstream. The present study focuses on the predictability of a Mediterranean tropical-like storm (Medicane) on 26 September 2006 downstream of the ET of Hurricane Helene from 22 to 25 September. While the development of the Medicane was missed in the deterministic forecasts from the European Centre for Medium-Range Weather Forecasts (ECMWF) initialized before and during ET, it was contained in the ECMWF ensemble forecasts in more than 10% of the 50 members up to 108-h lead time. The 200 ensemble members initialized at 0000 UTC from 20 to 23 September were clustered into two nearly equiprobable scenarios after the synoptic situation over the Mediterranean. In the first and verifying scenario, Helene was steered northeastward by an upstream trough during ET and contributed to the building of a downstream ridge. A trough elongated farther downstream toward Italy and enabled the development of the Medicane in 9 of 102 members. In the second and nonverifying scenario, Helene turned southeastward during ET and the downstream ridge building was reduced. A large-scale low over the British Isles dominated the circulation in Europe and only 1 of 98 members forecasted the Medicane. The two scenarios resulted from a different phasing between Helene and the upstream trough. Sensitivity experiments performed with the Méso-NH model further revealed that initial perturbations targeted on Helene and the upstream trough were sufficient in forecasting the warm-core Medicane at 84- and 108-h lead time.

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Ten years of the Wind Atlas of South Africa: Final results from WASA 3

10.5194/egusphere-egu21-6020 ◽

2021 ◽

Author(s):

Andrea Hahmann ◽

Chris Lennard ◽

Rogier Floors ◽

Dalibor Cavar ◽

Niels G. Mortensen ◽

...

Keyword(s):

South Africa ◽

Wind Speed ◽

Power Density ◽

Horizontal Resolution ◽

Data Sets ◽

Error Statistics ◽

Mean Power ◽

Mean Wind Speed ◽

Wind Climate

We present the evolution of the methods used to create and validate the various numerical wind atlases during the past ten years of the Wind Atlas for South Africa (WASA) project. In WASA 3, we improved on the previous numerical wind atlases by:<ul><li>Creating an ensemble of 2-year simulations to find the optimal set of parameterisations and surface conditions for the wind climate of South Africa.</li> <li>Using a new method of generalisation and downscaling of the WRF-derived wind climate using the PyWAsP engine.</li> <li>Producing the most extensive to date wind climatology for South Africa, 30 years (1990&#8211;2019) simulation covering all South Africa at 3.33 km &#215; 3.33 km spatial resolution and 30 minutes time output.</li> </ul>We will discuss these three areas and their improvements to the wind atlas' quality. The WASA 3 wind atlas' final error statistics show that the new WRF + PyWAsP method has a MAPE of 11.8% and 3.5% for the long-term mean power density and mean wind speed, respectively. These statistics are improved from those in WASA 1 and WASA 2.When disregarding the two masts (WM09 and WM11) located in highly complex terrain, where the methodology was never designed, the use of the WRF and WRF + PyWAsP downscaling narrows the error distributions for both long-term wind speed and power density compared to the global reanalysis, ERA5.The validated numerical wind atlas has further been used to model the wind resources of the entire land area of South Africa using the microscale WAsP model. Raster data exist with a horizontal resolution of 250 meters and three levels of 50, 100 and 150 meters a.g.l. of mean wind speed, power density, air density, Weibull A and k parameters, and ruggedness index.&#160; These data sets and the WRF dataset will be made available in the public domain at the end of the project. Data sets for other heights above the ground and offshore can easily be added later.

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Stochastic and Perturbed Parameter Representations of Model Uncertainty in Convection Parameterization*

Journal of the Atmospheric Sciences ◽

10.1175/jas-d-14-0250.1 ◽

2015 ◽

Vol 72 (6) ◽

pp. 2525-2544 ◽

Cited By ~ 37

Author(s):

H. M. Christensen ◽

I. M. Moroz ◽

T. N. Palmer

Keyword(s):

Model Uncertainty ◽

Ensemble Prediction ◽

Uncertain Parameters ◽

Convection Scheme ◽

Weather Forecasts ◽

Probabilistic Forecasts ◽

Medium Range ◽

Estimation System ◽

Convection Parameterization ◽

Parameter Scheme

Abstract It is now acknowledged that representing model uncertainty in atmospheric simulators is essential for the production of reliable probabilistic forecasts, and a number of different techniques have been proposed for this purpose. This paper presents new perturbed parameter schemes for use in the European Centre for Medium-Range Weather Forecasts (ECMWF) convection scheme. Two types of scheme are developed and implemented. Both schemes represent the joint uncertainty in four of the parameters in the convection parameterization scheme, which was estimated using the Ensemble Prediction and Parameter Estimation System (EPPES). The first scheme developed is a fixed perturbed parameter scheme, where the values of uncertain parameters are varied between ensemble members, but held constant over the duration of the forecast. The second is a stochastically varying perturbed parameter scheme. The performance of these schemes was compared to the ECMWF operational stochastic scheme, stochastically perturbed parameterization tendencies (SPPT), and to a model that does not represent uncertainty in convection. The skill of probabilistic forecasts made using the different models was evaluated. While the perturbed parameter schemes improve on the stochastic parameterization in some regards, the SPPT scheme outperforms the perturbed parameter approaches when considering forecast variables that are particularly sensitive to convection. Overall, SPPT schemes are the most skillful representations of model uncertainty owing to convection parameterization.

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Trajectory matching of ozonesondes and MOZAIC measurements in the UTLS – Part 2: Application to the global ozonesonde network

Atmospheric Measurement Techniques ◽

10.5194/amt-7-241-2014 ◽

2014 ◽

Vol 7 (1) ◽

pp. 241-266 ◽

Cited By ~ 9

Author(s):

J. Staufer ◽

J. Staehelin ◽

R. Stübi ◽

T. Peter ◽

F. Tummon ◽

...

Keyword(s):

Three Dimensional ◽

Data Sets ◽

Wind Fields ◽

Concentration Cell ◽

Weather Forecasts ◽

Long Term Stability ◽

Medium Range ◽

The Difference ◽

Long Term Trend

Abstract. Both balloon-borne electrochemical ozonesondes and MOZAIC (measurements of ozone, water vapour, carbon monoxide and nitrogen oxides by in-service Airbus aircraft) provide very valuable data sets for ozone studies in the upper troposphere/lower stratosphere (UTLS). Although MOZAIC's highly accurate UV-photometers are regularly inspected and recalibrated annually, recent analyses cast some doubt on the long-term stability of their ozone analysers. To investigate this further, we perform a 16 yr comparison (1994–2009) of UTLS ozone measurements from balloon-borne ozonesondes and MOZAIC. The analysis uses fully three-dimensional trajectories computed from ERA-Interim (European Centre for Medium-Range Weather Forecasts Re-analysis) wind fields to find matches between the two measurement platforms. Although different sensor types (Brewer-Mast and Electrochemical Concentration Cell ozonesondes) were used, most of the 28 launch sites considered show considerable differences of up to 25% compared to MOZAIC in the mid-1990s, followed by a systematic tendency to smaller differences of around 5–10% in subsequent years. The reason for the difference before 1998 remains unclear, but observations from both sondes and MOZAIC require further examination to be reliable enough for use in robust long-term trend analyses starting before 1998. According to our analysis, ozonesonde measurements at tropopause altitudes appear to be rather insensitive to changing the type of the Electrochemical Concentration Cell ozonesonde, provided the cathode sensing solution strength remains unchanged. Scoresbysund (Greenland) showed systematically 5% higher readings after changing from Science Pump Corporation sondes to ENSCI Corporation sondes, while a 1.0% KI cathode electrolyte was retained.

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Improvement of Medium-Range Forecasts Using the Analog-Dynamical Method

Monthly Weather Review ◽

10.1175/mwr-d-13-00250.1 ◽

2014 ◽

Vol 142 (4) ◽

pp. 1570-1587 ◽

Cited By ~ 8

Author(s):

Haipeng Yu ◽

Jianping Huang ◽

Jifan Chou

Keyword(s):

Lead Time ◽

Forecast Skill ◽

Forecast Errors ◽

Weather Forecasts ◽

Planetary Scale ◽

Anomaly Correlation Coefficient ◽

Systematic Correction ◽

Medium Range ◽

Dynamical Method ◽

Height Fields

Abstract This study further develops the analog-dynamical method and applies it to medium-range weather forecasts. By regarding the forecast field as a small disturbance superimposed on historical analog fields, historical analog errors can be used to estimate and correct forecast errors. This method is applied to 10-day forecasts from the Global and Regional Assimilation and Prediction System (GRAPES). Both the distribution of atmospheric circulation and the pattern of sea surface temperature (SST) are considered in choosing the analog samples from a historical dataset for 2001–10 based on NCEP Final (FNL) data. The results demonstrate that the analog-dynamical method greatly reduces forecast errors and extends the period of validity of the global 500-hPa height field by 0.8 days, which is superior to results obtained using systematic correction. The correction effect at 500 hPa is increasingly significant when the lead time increases. Although the analogs are selected using 500-hPa height fields, the forecast skill at all vertical levels is improved. The average increase of the anomaly correlation coefficient (ACC) is 0.07, and the root-mean-square error (RMSE) is decreased by 10 gpm on average at a lead time of 10 days. The magnitude of errors for most forecast fields, such as height, temperature, and kinetic energy is decreased considerably by inverse correction. The model improvement is primarily a result of improvement for planetary-scale waves, while the correction for synoptic-scale waves does not affect model forecast skill. As this method is easy to operate and transport to other sophisticated models, it could be appropriate for operational use.

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Effect of Mean Wind Speed Variations on Power Generation of Wind Farm

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.215-216.1298 ◽

2012 ◽

Vol 215-216 ◽

pp. 1298-1307

Author(s):

Chen Guo ◽

Yan He

Keyword(s):

Power Generation ◽

Wind Speed ◽

Wind Farm ◽

High Reliability ◽

Wind Farms ◽

Measured Data ◽

Data Sets ◽

Mean Wind Speed ◽

Relationship Of ◽

The Relationship

Through two methods, wind speed data sets sequence, the elements of which increased in Mean Wind Speed (MWS) orderly, are introduced first, and a numerical integration method depending on Weibull fitting result and power curve data to calculate Power Generation (PG) is proposed in this paper. Then, with measured data of 3 wind farms, PG with different heights are calculated and contrastive studies are made, employing the proposed data sets processing and PG calculating methods. Research results indicate that the PG calculating method has high reliability, and Equivalent Available Duration (EAD) increases about 50-60h when MWS increased by 0.1m/s. The results provide important basis for studies on the relationship of PG variation and measured data correction methods.

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