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Assessments of the relationships between crop productivity and climate change rely upon a combination of modelling and measurement. As part of this review, this relationship is discussed in the context of crop and climate simulation. Methods for linking these two types of models are reviewed, wit...


Challinor, Andrew J.Ewert, FrankArnold, S.Simelton, ElisabethFraser E[Crops and climate change: progress, trends, and challenges in simulating impacts and informing adaptation]Crops and climate change: progress, trends, and challenges in simulating impacts and informing adaptation

The prediction of climate variability and change requires the use of a range of simulation models. Multiple climate model simulations are needed to sample the inherent uncertainties in seasonal to centennial prediction. Because climate models are computationally expensive, there is a tradeoff bet...


Challinor, Andrew J.Osborne, Tom M.Shaffrey, LenWeller, HilaryMorse, AndyWheeler, TimVidale, Pier Luigi[Methods and resources for climate impacts research]Methods and resources for climate impacts research

Global climate models (GCMs) have become increasingly important for climate change science and provide the basis for most impact studies. Since impact models are highly sensitive to input climate data, GCM skill is crucial for getting better short-, medium- and long-term outlooks for agricultural...


Ramírez Villegas, JuliánChallinor, Andrew J.Thornton, Philip K.Jarvis, Andy[Implications of regional improvement in global climate models for agricultural impact research]Implications of regional improvement in global climate models for agricultural impact research

Estimates of the response of crops to climate change rarely quantify the uncertainty inherent in the simulation of both climate and crops. We present a crop simulation ensemble for a location in India, perturbing the response of both crop and climate under both baseline (12 720 simulations) and d...


Challinor, Andrew J.Wheeler, TimHemming DUpadhyaya, Hari D.[Ensemble yield simulations: crop and climate uncertainties, sensitivity to temperature and genotypic adaptation to climate change]Ensemble yield simulations: crop and climate uncertainties, sensitivity to temperature and genotypic adaptation to climate change

The increasing use of multi-member climate model ensembles for making future climate impact assessments presents both opportunities for understanding uncertainties, and challenges for interpreting the results. We outline current approaches to assessing uncertainties in climate impacts, statistica...


Falloon, P.Challinor, Andrew J.Dessai, S.Hoang LJohnson JKöhler, Ann-Kristin[Ensembles and uncertainty in climate change impacts]Ensembles and uncertainty in climate change impacts

In order for climate forecasting to be used in developing adaptation options, the forecasts should be able to affect decisions made by stakeholders in a manner that improves outcomes. The implications of this requirement for forecasting are presented under five headings: relevance, reliability, s...


Challinor, Andrew J.[Towards the development of adaptation options using climate and crop yield forecasting at seasonal to multi-decadal timescales]Towards the development of adaptation options using climate and crop yield forecasting at seasonal to multi-decadal timescales

When projecting future crop production, the skill of regional scale (>100 km resolution) crop models is limited by the spatial and temporal accuracy of the calibration and weather data used. The skill of climate models in reproducing surface properties such as mean temperature and rainfall patter...


Watson, J.Challinor, Andrew J.[The relative importance of rainfall, temperature and yield data for a regional scale crop model]The relative importance of rainfall, temperature and yield data for a regional scale crop model
Wallach, DanielThorburn, Peter J.Asseng, SentholdChallinor, Andrew J.Ewert, FrankJones, James W.Rotter, Reimund P.Ruane, Alex C.[Estimating model prediction error: Should you treat predictions as fixed or random?]Estimating model prediction error: Should you treat predictions as fixed or random?

Using a global atmospheric chemistry model, we have quantified for the first time, intercontinental transboundary contributions to crop ozone exposure and subsequent yield reductions in the Northern Hemisphere. We apply four metrics (AOT40, M7, M12, W126) to assess the impacts of 100% reductions ...


Hollaway MJArnold, S.R.Challinor, Andrew J.Emberson LD[Intercontinental trans-boundary contributions to ozone-induced crop yield losses in the Northern Hemisphere]Intercontinental trans-boundary contributions to ozone-induced crop yield losses in the Northern Hemisphere

As climate changes, temperatures will play an increasing role in determining crop yield. Both climate model error and lack of constrained physiological thresholds limit the predictability of yield. We used a perturbed-parameter climate model ensemble with two methods of bias-correction as input t...


Köhler, Ann-KristinChallinor, Andrew J.Hawkins EAsseng, Senthold[Influences of increasing temperature on Indian wheat: quantifying limits to predictability]Influences of increasing temperature on Indian wheat: quantifying limits to predictability

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