A review on statistical postprocessing methods for hydrometeorological ensemble forecasting
Computer simulation models have been widely used to generate hydrometeorological
forecasts. As the raw forecasts contain uncertainties arising from various sources, including …
forecasts. As the raw forecasts contain uncertainties arising from various sources, including …
[HTML][HTML] 我国无缝隙精细化网格天气预报技术进展与挑战
金荣花， 代刊， 赵瑞霞， 曹勇， 薛峰， 刘凑华， 赵声蓉… - 气象, 2019 - qxqk.nmc.cn
本文总结了2014 年以来我国无缝隙精细化网格天气预报业务的技术进展,
讨论了未来发展所面临的关键技术难点. 无缝隙精细化网格预报技术的发展 …
讨论了未来发展所面临的关键技术难点. 无缝隙精细化网格预报技术的发展 …
Using artificial neural networks for generating probabilistic subseasonal precipitation forecasts over California
M Scheuerer, MB Switanek… - Monthly Weather …, 2020 - journals.ametsoc.org
Forecast skill of numerical weather prediction (NWP) models for precipitation accumulations
over California is rather limited at subseasonal time scales, and the low signal-to-noise ratio …
over California is rather limited at subseasonal time scales, and the low signal-to-noise ratio …
A novel hybrid artificial neural network-parametric scheme for postprocessing medium-range precipitation forecasts
Many present-day statistical schemes for postprocessing weather forecasts, in particular
precipitation forecasts, rely on calibration using prescribed statistical models to relate …
precipitation forecasts, rely on calibration using prescribed statistical models to relate …
Distributional regression forests for probabilistic precipitation forecasting in complex terrain
Supplement A: Different response distributions. To assess the goodness of fit of the
Gaussian distribution, left-censored at zero, this supplement employs the same evaluations …
Gaussian distribution, left-censored at zero, this supplement employs the same evaluations …
Reliability of ensemble climatological forecasts
Ensemble climatological forecasts play a critical part in benchmarking the predictive
performance of hydroclimatic forecasts. Accounting for the skewness and censoring …
performance of hydroclimatic forecasts. Accounting for the skewness and censoring …
Nonhomogeneous boosting for predictor selection in ensemble postprocessing
Nonhomogeneous regression is often used to statistically postprocess ensemble forecasts.
Usually only ensemble forecasts of the predictand variable are used as input, but other …
Usually only ensemble forecasts of the predictand variable are used as input, but other …
A smart post-processing system for forecasting the climate precipitation based on machine learning computations
A Ghazikhani, I Babaeian, M Gheibi… - Sustainability, 2022 - mdpi.com
Although many meteorological prediction models have been developed recently, their
accuracy is still unreliable. Post-processing is a task for improving meteorological …
accuracy is still unreliable. Post-processing is a task for improving meteorological …
[HTML][HTML] Spatio‐temporal precipitation climatology over complex terrain using a censored additive regression model
Flexible spatio‐temporal models are widely used to create reliable and accurate estimates
for precipitation climatologies. Most models are based on square root transformed monthly …
for precipitation climatologies. Most models are based on square root transformed monthly …
A five-parameter Gamma-Gaussian model to calibrate monthly and seasonal GCM precipitation forecasts
Calibration is necessary for improving raw forecasts generated by global climate models
(GCMs) to fully utilize potential benefits of the forecasts in practical applications. Based on …
(GCMs) to fully utilize potential benefits of the forecasts in practical applications. Based on …