Crop multi-model ensembles (MME) have proven to be effective in increasing the accuracy of simulations in modelling experiments. However, the ability of a MME to capture crop response to changes in sowing dates and densities has not yet been investigated. These management interventions are some of the main levers for adapting cropping systems to climate change. Here, we explore the performance of a MME of 29 wheat crop models to predict the effect of changing sowing dates and rates on yield and yield components, on two sites located in a high-yielding environment in New Zealand. The experiment was conducted for 6 years and provided 50 combinations of sowing date, sowing density and growing season.". We show that the MME simulates seasonal g...
Robustness of four wheat simulation model were tested with 2-year field experiments of three cultiva...
Impact response surfaces (IRSs) were constructed to depict the sensitivity of modelled spring and wi...
Rising temperatures reduce global wheat production S. Asseng et al.† Crop models are essential tools...
International audienceCrop multi-model ensembles (MME) have proven to be effective in increasing the...
The dataset contains 6 growing seasons of a local winter wheat cultivar ‘Wakanui’ at two farms locat...
Crop models are essential tools for assessing the threat of climate change to local and global food ...
Crop models are essential tools for assessing the threat of climate change to local and global food ...
To improve climate change impact estimates and to quantify their uncertainty, multi-model ensembles ...
Projections of climate change impacts on crop performances are inherently uncertain. However, multim...
To improve climate change impact estimates and to quantify their uncertainty, multi-model ensembles ...
We compare 27 wheat models' yield responses to interannual climate variability, analyzed at location...
We compare 27 wheat models' yield responses to interannual climate variability, analyzed at location...
Robustness of four wheat simulation model were tested with 2-year field experiments of three cultiva...
Impact response surfaces (IRSs) were constructed to depict the sensitivity of modelled spring and wi...
Rising temperatures reduce global wheat production S. Asseng et al.† Crop models are essential tools...
International audienceCrop multi-model ensembles (MME) have proven to be effective in increasing the...
The dataset contains 6 growing seasons of a local winter wheat cultivar ‘Wakanui’ at two farms locat...
Crop models are essential tools for assessing the threat of climate change to local and global food ...
Crop models are essential tools for assessing the threat of climate change to local and global food ...
To improve climate change impact estimates and to quantify their uncertainty, multi-model ensembles ...
Projections of climate change impacts on crop performances are inherently uncertain. However, multim...
To improve climate change impact estimates and to quantify their uncertainty, multi-model ensembles ...
We compare 27 wheat models' yield responses to interannual climate variability, analyzed at location...
We compare 27 wheat models' yield responses to interannual climate variability, analyzed at location...
Robustness of four wheat simulation model were tested with 2-year field experiments of three cultiva...
Impact response surfaces (IRSs) were constructed to depict the sensitivity of modelled spring and wi...
Rising temperatures reduce global wheat production S. Asseng et al.† Crop models are essential tools...