Crop yields are sensitive to extreme weather events. Improving the understanding of the mechanisms and the drivers of the projection uncertainties can help to improve decisions. Previous studies have provided important insights, but often sample only a small subset of potentially important uncertainties. Here we expand on a previous statistical modeling approach by refining the analyses of two uncertainty sources. Specifically, we assess the effects of uncertainties surrounding crop-yield model parameters and climate forcings on projected crop yield. We focus on maize yield projections in the eastern U.S.in this century. We quantify how considering more uncertainties expands the lower tail of yield projections. We characterized the relative...
Scientific challenges exist on how to extract information from the wide range of projected impacts s...
We present maize production in sub-Saharan Africa as a case study in the exploration of how uncertai...
This study investigates the main drivers of uncertainties in simulated irrigated maize yield under h...
Crop yields are sensitive to extreme weather events. Improving the understanding of the mechanisms a...
Being able to predict potential food shortages is of vital importance. The more extreme the weather,...
<p><strong>Figure 4.</strong> Uncertainty decomposition for yield using the simulations including HT...
One of the sources of uncertainty in simulating the plausible impacts of climate change on crop pr...
Pervious assessments of crop yield response to climate change are mainly aided with either process-b...
peer reviewedConcerns over climate change are motivated in large part because of their impact on hum...
The impact of adverse weather conditions (AWCs) on crop production is random in both time and space ...
Global gridded crop models (GGCMs) are the workhorse of assessments of the agricultural impacts of c...
<p><strong>Figure 1.</strong> 2050–2069 mean yield minus the simulated baseline yield. Future simula...
Global gridded crop models (GGCMs) are the workhorse of assessments of the agricultural impacts of c...
Projections of future food production necessarily rely on models, which must themselves be validated...
Potential consequences of climate change on crop production can be studied using mechanistic crop si...
Scientific challenges exist on how to extract information from the wide range of projected impacts s...
We present maize production in sub-Saharan Africa as a case study in the exploration of how uncertai...
This study investigates the main drivers of uncertainties in simulated irrigated maize yield under h...
Crop yields are sensitive to extreme weather events. Improving the understanding of the mechanisms a...
Being able to predict potential food shortages is of vital importance. The more extreme the weather,...
<p><strong>Figure 4.</strong> Uncertainty decomposition for yield using the simulations including HT...
One of the sources of uncertainty in simulating the plausible impacts of climate change on crop pr...
Pervious assessments of crop yield response to climate change are mainly aided with either process-b...
peer reviewedConcerns over climate change are motivated in large part because of their impact on hum...
The impact of adverse weather conditions (AWCs) on crop production is random in both time and space ...
Global gridded crop models (GGCMs) are the workhorse of assessments of the agricultural impacts of c...
<p><strong>Figure 1.</strong> 2050–2069 mean yield minus the simulated baseline yield. Future simula...
Global gridded crop models (GGCMs) are the workhorse of assessments of the agricultural impacts of c...
Projections of future food production necessarily rely on models, which must themselves be validated...
Potential consequences of climate change on crop production can be studied using mechanistic crop si...
Scientific challenges exist on how to extract information from the wide range of projected impacts s...
We present maize production in sub-Saharan Africa as a case study in the exploration of how uncertai...
This study investigates the main drivers of uncertainties in simulated irrigated maize yield under h...