Hindcast data from the University of Reading Empirical Climate Model Version 1.0 (UREAD-ECM1.0): Decadal Prediction Experiment. Each zip file contains ensemble hindcast data for annual mean (Jan-Dec) surface air temperature anomalies covering the period 1960-2014, with start dates every year, generated from the UREAD empirical model. The data is intended as a benchmark model for the decadal prediction experiments. Each hindcast set is generated using a different prediction mode. The `standard� model configuration data also contains a forecast ensemble covering the period 2016-2025 (with a 2015 launch date). All anomalies are given relative to the mean of 1961-1990. For more information about the model and experimental design see: E. Su...
We start with the yearly averaged temperature anomaly, volume averaged (over a basin) at observed lo...
Can today's global climate model ensembles characterize the 21st century climate in their own 'model...
Climate predictions using coupled models in different time scales, from intraseasonal to decadal, ar...
Hindcast data from the University of Reading Empirical Climate Model Version 1.0 (UREAD-ECM1.0): Dec...
While state-of-the-art models of Earth's climate system have improved tremendously over the last 20 ...
Decadal climate prediction is a challenging aspect of climate research. It has been and will be tack...
There are two main approaches for dealing with model biases in forecasts made with initialized clima...
This dataset is the output of the National Center for Atmospheric Research (NCAR) Community Earth Sy...
An ensemble of yearly initialized decadal predictions is performed with the Max Planck Institute Ear...
In initialized seasonal to decadal (S2D) predictions, model hindcasts rapidly drift away from the in...
Decadal climate predictions are being increasingly used by stakeholders interested in the evolution ...
Decadal climate prediction is a branch of climate modelling with the theoretical potential to antici...
© Copyright 2009 American Meteorological Society (AMS). Permission to use figures, tables, and brief...
This paper provides an update on research in the relatively new and fast-moving field of decadal cli...
The data represents time series of seasonal weather forecasts for rainfall and temperature. The data...
We start with the yearly averaged temperature anomaly, volume averaged (over a basin) at observed lo...
Can today's global climate model ensembles characterize the 21st century climate in their own 'model...
Climate predictions using coupled models in different time scales, from intraseasonal to decadal, ar...
Hindcast data from the University of Reading Empirical Climate Model Version 1.0 (UREAD-ECM1.0): Dec...
While state-of-the-art models of Earth's climate system have improved tremendously over the last 20 ...
Decadal climate prediction is a challenging aspect of climate research. It has been and will be tack...
There are two main approaches for dealing with model biases in forecasts made with initialized clima...
This dataset is the output of the National Center for Atmospheric Research (NCAR) Community Earth Sy...
An ensemble of yearly initialized decadal predictions is performed with the Max Planck Institute Ear...
In initialized seasonal to decadal (S2D) predictions, model hindcasts rapidly drift away from the in...
Decadal climate predictions are being increasingly used by stakeholders interested in the evolution ...
Decadal climate prediction is a branch of climate modelling with the theoretical potential to antici...
© Copyright 2009 American Meteorological Society (AMS). Permission to use figures, tables, and brief...
This paper provides an update on research in the relatively new and fast-moving field of decadal cli...
The data represents time series of seasonal weather forecasts for rainfall and temperature. The data...
We start with the yearly averaged temperature anomaly, volume averaged (over a basin) at observed lo...
Can today's global climate model ensembles characterize the 21st century climate in their own 'model...
Climate predictions using coupled models in different time scales, from intraseasonal to decadal, ar...