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Advance and prospectus of seasonal prediction: assessment of the APCC/CliPAS 14-model ensemble retrospective seasonal prediction (1980–2004)
We assessed current status of multi-model ensemble (MME) deterministic and probabilistic
seasonal prediction based on 25-year (1980–2004) retrospective forecasts performed by 14 …
seasonal prediction based on 25-year (1980–2004) retrospective forecasts performed by 14 …
Evaluation of the CORDEX-Africa multi-RCM hindcast: systematic model errors
Monthly-mean precipitation, mean (T AVG), maximum (T MAX) and minimum (T MIN) surface
air temperatures, and cloudiness from the CORDEX-Africa regional climate model (RCM) …
air temperatures, and cloudiness from the CORDEX-Africa regional climate model (RCM) …
The rationale behind the success of multi-model ensembles in seasonal forecasting—II. Calibration and combination
FJ Doblas-Reyes, R Hagedorn… - Tellus A: Dynamic …, 2005 - Taylor & Francis
The DEMETER multi-model ensemble system is used to investigate the enhancement in
seasonal predictability that can be achieved by calibrating single-model ensembles and …
seasonal predictability that can be achieved by calibrating single-model ensembles and …
A Streamflow Forecasting Framework using Multiple Climate and Hydrological Models1
Water resources planning and management efficacy is subject to capturing inherent
uncertainties stemming from climatic and hydrological inputs and models. Streamflow …
uncertainties stemming from climatic and hydrological inputs and models. Streamflow …
[HTML][HTML] The physics of space weather/solar-terrestrial physics (STP): what we know now and what the current and future challenges are
Major geomagnetic storms are caused by unusually intense solar wind southward magnetic
fields that im**e upon the Earth's magnetosphere (Dungey, 1961). How can we predict the …
fields that im**e upon the Earth's magnetosphere (Dungey, 1961). How can we predict the …
Improving estimates of population status and trend with superensemble models
Fishery managers must often reconcile conflicting estimates of population status and trend.
Superensemble models, commonly used in climate and weather forecasting, may provide …
Superensemble models, commonly used in climate and weather forecasting, may provide …
Projecting global fertilizer consumption under shared socioeconomic pathway (SSP) scenarios using an approach of ensemble machine learning
Y Gao, K Dong, Y Yue - Science of The Total Environment, 2024 - Elsevier
Comprehensively projecting global fertilizer consumption is essential for providing critical
datasets in related fields such as earth system simulation, the fertilizer industry, and …
datasets in related fields such as earth system simulation, the fertilizer industry, and …
Two deep learning-based bias-correction pathways improve summer precipitation prediction over China
As most global climate models (GCM) suffer from large biases in simulating/predicting
summer precipitation over China, it is of great importance to develop suitable bias-correction …
summer precipitation over China, it is of great importance to develop suitable bias-correction …
Multimodel ensemble forecasts of precipitation based on an object-based diagnostic evaluation
We analyzed 24-h accumulated precipitation forecasts over the 4-month period from 1 May
to 31 August 2013 over an area located in East Asia covering the region 15.05°–58.95° N …
to 31 August 2013 over an area located in East Asia covering the region 15.05°–58.95° N …
Assessment of the APCC coupled MME suite in predicting the distinctive climate impacts of two flavors of ENSO during boreal winter
Forecast skill of the APEC Climate Center (APCC) Multi-Model Ensemble (MME) seasonal
forecast system in predicting two main types of El Niño-Southern Oscillation (ENSO), namely …
forecast system in predicting two main types of El Niño-Southern Oscillation (ENSO), namely …