Comparison of Probabilistic Post-Processing Approaches for Improving Numerical Weather Prediction-Based Daily and Weekly Reference Evapotranspiration Forecasts

Hydrology and Earth System Sciences - Germany
doi 10.5194/hess-24-1011-2020
Full Text
Abstract

Available in full text

Date
Authors
Publisher

Copernicus GmbH

Related search

Comparison of Probabilistic Post-Processing Approaches for Improving NWP-based Daily and Weekly Reference Evapotranspiration Forecasts

2019English

An Evaluation of Numerical Weather Prediction Based Rainfall Forecasts

Hydrological Sciences Journal
Water ScienceTechnology
2016English

H∞ Filtering for Bias Correction in Post-Processing of Numerical Weather Prediction

Journal of the Meteorological Society of Japan
Atmospheric Science
2019English

Improving Wintertime Low Level Cloud Forecasts in a High Resolution Numerical Weather Prediction Model

Idojaras
Atmospheric Science
2019English

Statistical Forecasts Based on the National Meteorological Center's Numerical Weather Prediction System

Weather and Forecasting
Atmospheric Science
1989English

Mesoscale Forecasts Generated From Operational Numerical Weather-Prediction Model Output

Bulletin of the American Meteorological Society
Atmospheric Science
1988English

Improved Seasonal Drought Forecasts Using Reference Evapotranspiration Anomalies

Geophysical Research Letters
EarthPlanetary SciencesGeophysics
2016English

Evaluation of Numerical Weather Prediction Model Precipitation Forecasts for Use in Short-Term Streamflow Forecasting

Hydrology and Earth System Sciences Discussions
EarthEarth-Surface ProcessesPlanetary Sciences
2012English

Evaluation of Machine Learning Techniques for Daily Reference Evapotranspiration Estimation

2019English

Amanote Research

Note-taking for researchers

Follow Amanote

© 2024 Amaplex Software S.P.R.L. All rights reserved.

Privacy PolicyRefund Policy