Ensemble simulations from the weather and climate model COSMO. The data has been used for model verification cases in the corresponding paper (https://doi.org/10.5194/gmd-2021-248). The data is partitioned into the following parts: gpu_dycore.tar.gz 5-day ensemble (600 members) produced with COSMO 5.09 GPU version in double precision. cpu_nodycore.tar.gz 5-day ensemble (200 members) produced with COSMO 5.09 CPU version in double precision. gpu_dycore_sp.tar.gz 5-day ensemble (200 members) produced with COSMO 5.09 GPU version in single precision. The second part of the dataset with the diffusion ensembles can be found here: https://doi.org/10.5281/zenodo.635564
A statistical framework for comparing the output of ensemble simulations from global climate models ...
Abstract—Given very large volumes of remote sensing data and climate model output, one would like to...
Complex, modular codes such as climate simulations are in a constant state of development, requiring...
Ensemble simulations from the weather and climate model COSMO. The data has been used for model veri...
Since their first operational application in the 1950s, atmospheric numerical models have become ess...
End users studying impacts and risks caused by human-induced climate change are often presented with...
This dataset was created from perturbed parameter ensembles (PPEs) using HadGEM-UKCA atmospheric com...
Climate simulation codes, such as the Community Earth System Model (CESM), are especially complex an...
This study examines the subset climate model ensemble size required to reproduce certain statistical...
An ensemble of models can be interpreted in two ways. The first treats each model as an approximatio...
International audienceLarge ensembles of model simulations require considerable resources, and thus ...
This study describes the experimental setup of an atmospheric ensemble prediction system (EPS) based...
In climate science, observational gridded climate datasets that are based on in situ measurements se...
COSMO-SREPS (csreps) is a high-resolution ensemble system for the short-range (up to three days). Th...
Global climate models (GCMs) contain imprecisely defined parameters that account, approximately, for...
A statistical framework for comparing the output of ensemble simulations from global climate models ...
Abstract—Given very large volumes of remote sensing data and climate model output, one would like to...
Complex, modular codes such as climate simulations are in a constant state of development, requiring...
Ensemble simulations from the weather and climate model COSMO. The data has been used for model veri...
Since their first operational application in the 1950s, atmospheric numerical models have become ess...
End users studying impacts and risks caused by human-induced climate change are often presented with...
This dataset was created from perturbed parameter ensembles (PPEs) using HadGEM-UKCA atmospheric com...
Climate simulation codes, such as the Community Earth System Model (CESM), are especially complex an...
This study examines the subset climate model ensemble size required to reproduce certain statistical...
An ensemble of models can be interpreted in two ways. The first treats each model as an approximatio...
International audienceLarge ensembles of model simulations require considerable resources, and thus ...
This study describes the experimental setup of an atmospheric ensemble prediction system (EPS) based...
In climate science, observational gridded climate datasets that are based on in situ measurements se...
COSMO-SREPS (csreps) is a high-resolution ensemble system for the short-range (up to three days). Th...
Global climate models (GCMs) contain imprecisely defined parameters that account, approximately, for...
A statistical framework for comparing the output of ensemble simulations from global climate models ...
Abstract—Given very large volumes of remote sensing data and climate model output, one would like to...
Complex, modular codes such as climate simulations are in a constant state of development, requiring...