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Wind gust prediction plays an important role in warning strategies of national meteorological services due to the high impact of its extreme values.
Verification of forecasts expressed in terms of probability
Brier, G. W. (1950) · 1950
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On subjective probability forecasting
Sanders, F. (1963) · 1963
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Calibrated probabilistic forecasting using ensemble model output statistics and minimum CRPS estimation
Gneiting, T., Raftery, A. E., Westveld, A. H. and Goldman, T. (2005) · 2005
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Probabilistic forecasts, calibration and sharpness
Gneiting, T., Balabdaoui, F. and Raftery, A. E. (2007) · 2007
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Experimental ensemble forecasts of precipitation based on a convection-resolving model
Gebhardt, C., Theis, S., Krahe, P. and Renner, V. (2008) · 2008
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Operational Convective Scale Numerical Weather Prediction with the COSMO Model Description and Sensitivities
Baldauf, M., Seifert, A., Förstner, J., Majewski, D., Raschendorfer, M. and Reinhardt, T. (2011) · 2011
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Accounting for initial condition uncertainties in COSMO-DE-EPS
Peralta, C., Ben Bouallègue, Z., Theis, S. E., Gebhardt, C. and Buchhold, M. (2012) · 2012
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ModelMIX – Optimal Combination of NWP Model Forecasts for AutoWARN
Hirsch, T., Hess, R., Trepte, S., Primo, C., Glashoff, J., Reichert, B. and Heizenreder, D. (2014) · 2014
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Kilometre-scale ensemble data assimilation for the COSMO model (KENDA)
Schraff, C., Reich, H., Rhodin, A., Schomburg, A., Stephan, K., Periáñez, A. and Potthast, R. (2016) · 2016
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Forecaster’s dilemma: Extreme events and forecast evaluation
Lerch, S., Thorarinsdottir, T. L., Ravazzolo, F. and Gneiting, T. (2017) · 2017
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Nonhomogeneous boosting for predictor selection in ensemble postprocessing
Messner, J. W., Mayr, G. J. and Zeileis, A. (2017) · 2017
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Forecasting wind gusts in winter storms using a calibrated convection-permitting ensemble
Pantillon, F., Lerch, S., Knippertz, P. and Corsmeier, U. (2018) · 2018
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Neural networks for postprocessing ensemble weather forecasts
Rasp, S. and Lerch, S. (2018) · 2018
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Statistical Postprocessing of Ensemble Forecasts
Vannitsem, S., Wilks, D. S. and Messner, J. W. (2018) · 2018
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Towards implementing artificial intelligence post-processing in weather and climate: Proposed actions from the Oxford 2019 workshop
Haupt, S. E., Chapman, W., Adams, S. V., Kirkwood, C., Hosking, J. S., Robinson, N. H., Lerch, S. and Subramanian, A. C. (2021) · 2019
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A novel hybrid artificial neural network-parametric scheme for postprocessing medium-range precipitation forecasts
Ghazvinian, M., Zhang, Y., Seo, D.-J., He, M. and Fernando, N. (2021) · 2021
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Statistical postprocessing for weather forecasts: Review, challenges, and avenues in a big data world
Vannitsem, S., Bremnes, J. B., Demaeyer, J., Evans, G. R., Flowerdew, J., Hemri, S., Lerch, S., Roberts, N., Theis, S., Atencia, A., Bouallègue, Z. B., Bhend, J., Dabernig, M., Cruz, L. D., Hieta, L., Mestre, O., Moret, L., Plenković, I. O., Schmeits, M., Taillardat, M., den Bergh, J. V., Schaeybroeck, B. V., Whan, K. and Ylhaisi, J. (2021) · 2021
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Statistical postprocessing of wind speed forecasts using convolutional neural networks
Veldkamp, S., Whan, K., Dirksen, S. and Schmeits, M. (2021) · 2021
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A comprehensive survey on transfer learning
Zhuang, F., Qi, Z., Duan, K., Xi, D., Zhu, Y., Zhu, H., Xiong, H. and He, Q. (2021) · 2021
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Probabilistic predictions from deterministic atmospheric river forecasts with deep learning
Chapman, W. E., Monache, L. D., Alessandrini, S., Subramanian, A. C., Ralph, F. M., Xie, S.-P., Lerch, S. and Hayatbini, N. (2022) · 2022
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Ensemble postprocessing using quantile function regression based on neural networks and Bernstein polynomials
Bremnes, J. B. (2020) · 2020
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Statistical postprocessing of ensemble forecasts for severe weather at Deutcher Wetterdienst
Hess, R. (2020) · 2020
Cited alongside, same era.
Remember the past: a comparison of time-adaptive training schemes for non-homogeneous regression
Lang, M. N., Lerch, S., Mayr, G. J., Simon, T., Stauffer, R. and Zeileis, A. (2020) · 2020
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Using artificial neural networks for generating probabilistic subseasonal precipitation forecasts over California
Scheuerer, M., Switanek, M. B., Worsnop, R. P. and Hamill, T. M. (2020) · 2020
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Machine learning for total cloud cover prediction
Baran, A., Lerch, S., El Ayari, M. and Baran, S. (2021) · 2021
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Machine learning methods for postprocessing ensemble forecasts of wind gusts: A systematic comparison
Schulz, B. and Lerch, S. (2022) · 2022
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Probabilistic solar forecasting: Benchmarks, post-processing, verification
Gneiting, T., Schulz, B. and Lerch, S. (2023) · 2023
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Deep learning for post-processing global probabilistic forecasts on sub-seasonal time scales
Horat, N. and Lerch, S. (2023) · 2023
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Postprocessing of ensemble weather forecasts using permutation-invariant neural networks
Höhlein, K., Schulz, B., Westermann, R. and Lerch, S. (2023) · 2023
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DWD database reference for the global and regional ICON and ICON-EPS forecasting system.
Reinert, D., Prill, F., Frank, H., Denhard, M., Baldauf, M., Schraff, C., Gebhardt, C., Marsigli, C. and Zängl, G. (2023) · 2023
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