129 citations · 818 across the 33 of their papers we have counts for
33 papers
Statistical post-processing of visibility ensemble forecasts
Sándor Baran, Mária Lakatos
To be able to produce accurate and reliable predictions of visibility has crucial importance in aviation meteorology, as well as in water- and road transportation. Nowadays, severa…
Parametric post-processing of dual-resolution precipitation forecasts
Marianna Szabó, Estíbaliz Gascón, Sándor Baran
Recently, all major weather centres issue ensemble forecasts which even covering the same domain differ both in the ensemble size and spatial resolution. These two parameters highl…
A two-step machine learning approach to statistical post-processing of weather forecasts for power generation
Ágnes Baran, Sándor Baran
By the end of 2021, the renewable energy share of the global electricity capacity reached 38.3% and the new installations are dominated by wind and solar energy, showing global inc…
Comparison of multivariate post-processing methods using global ECMWF ensemble forecasts
Mária Lakatos, Sebastian Lerch, Stephan Hemri +1
An influential step in weather forecasting was the introduction of ensemble forecasts in operational use due to their capability to account for the uncertainties in the future stat…
Calibration of wind speed ensemble forecasts for power generation
Sándor Baran, Ágnes Baran
In the last decades wind power became the second largest energy source in the EU covering 16% of its electricity demand. However, due to its volatility, accurate short range wind p…
Post-processing numerical weather prediction ensembles for probabilistic solar irradiance forecasting
Benedikt Schulz, Mehrez El Ayari, Sebastian Lerch +1
In order to enable the transition towards renewable energy sources, probabilistic energy forecasting is of critical importance for incorporating volatile power sources such as sola…
Truncated generalized extreme value distribution based EMOS model for calibration of wind speed ensemble forecasts
Sándor Baran, Patrícia Szokol, Marianna Szabó
In recent years, ensemble weather forecasting have become a routine at all major weather prediction centres. These forecasts are obtained from multiple runs of numerical weather pr…
Statistical post-processing of heat index ensemble forecasts: is there a royal road?
Sándor Baran, Ágnes Baran, Florian Pappenberger +1
We investigate the effect of statistical post-processing on the probabilistic skill of discomfort index (DI) and indoor wet-bulb globe temperature (WBGTid) ensemble forecasts, both…
Machine learning for total cloud cover prediction
Ágnes Baran, Sebastian Lerch, Mehrez El Ayari +1
Accurate and reliable forecasting of total cloud cover (TCC) is vital for many areas such as astronomy, energy demand and production, or agriculture. Most meteorological centres is…
Statistical post-processing of dual-resolution ensemble forecasts
Sándor Baran, Martin Leutbecher, Marianna Szabó +1
The computational cost as well as the probabilistic skill of ensemble forecasts depends on the spatial resolution of the numerical weather prediction model and the ensemble size. P…
Statistical post-processing of ensemble forecasts of temperature in Santiago de Chile
Mailiu Díaz, Orietta Nicolis, Julio César Marín +1
Currently all major meteorological centres generate ensemble forecasts using their operational ensemble prediction systems; however, it is a general problem that the spread of the…
Statistical post-processing of hydrological forecasts using Bayesian model averaging
Sándor Baran, Stephan Hemri, Mehrez El Ayari
Accurate and reliable probabilistic forecasts of hydrological quantities like runoff or water level are beneficial to various areas of society. Probabilistic state-of-the-art hydro…
On the optimal designs for the prediction of complex Ornstein-Uhlenbeck processes
Kinga Sikolya, Sándor Baran
Physics, chemistry, biology or finance are just some examples out of the many fields where complex Ornstein-Uhlenbeck (OU) processes have various applications in statistical modell…
D-optimal designs for complex Ornstein-Uhlenbeck processes
Sándor Baran, Csilla Szák-Kocsis, Milan Stehlík
Complex Ornstein-Uhlenbeck (OU) processes have various applications in statistical modelling. They play role e.g. in the description of the motion of a charged test particle in a c…
Combining predictive distributions for statistical post-processing of ensemble forecasts
Sándor Baran, Sebastian Lerch
Statistical post-processing techniques are now widely used to correct systematic biases and errors in calibration of ensemble forecasts obtained from multiple runs of numerical wea…
K-optimal designs for parameters of shifted Ornstein-Uhlenbeck processes and sheets
Sándor Baran
Continuous random processes and fields are regularly applied to model temporal or spatial phenomena in many different fields of science, and model fitting is usually done with the…
Censored and shifted gamma distribution based EMOS model for probabilistic quantitative precipitation forecasting
Sándor Baran, Dóra Nemoda
Recently all major weather prediction centres provide forecast ensembles of different weather quantities which are obtained from multiple runs of numerical weather prediction model…
Similarity-based semi-local estimation of EMOS models
Sebastian Lerch, Sandor Baran
Weather forecasts are typically given in the form of forecast ensembles obtained from multiple runs of numerical weather prediction models with varying initial conditions and physi…
Bivariate ensemble model output statistics approach for joint forecasting of wind speed and temperature
Sándor Baran, Annette Möller
Forecast ensembles are typically employed to account for prediction uncertainties in numerical weather prediction models. However, ensembles often exhibit biases and dispersion err…
Mixture EMOS model for calibrating ensemble forecasts of wind speed
Sándor Baran, Sebastian Lerch
Ensemble model output statistics (EMOS) is a statistical tool for post-processing forecast ensembles of weather variables obtained from multiple runs of numerical weather predictio…
Log-normal distribution based EMOS models for probabilistic wind speed forecasting
Sándor Baran, Sebastian Lerch
Ensembles of forecasts are obtained from multiple runs of numerical weather forecasting models with different initial conditions and typically employed to account for forecast unce…
Joint probabilistic forecasting of wind speed and temperature using Bayesian model averaging
Sándor Baran, Annette Möller
Ensembles of forecasts are typically employed to account for the forecast uncertainties inherent in predictions of future weather states. However, biases and dispersion errors ofte…
Optimal designs for the methane flux in troposphere
Sándor Baran, Kinga Sikolya, Milan Stehlík
The understanding of methane emission and methane absorption plays a central role both in the atmosphere and on the surface of the Earth. Several important ecological processes, e.…
Comparison of BMA and EMOS statistical calibration methods for temperature and wind speed ensemble weather prediction
Sándor Baran, András Horányi, Dóra Nemoda
The evolution of the weather can be described by deterministic numerical weather forecasting models. Multiple runs of these models with different initial conditions and/or model ph…