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Predicting yields using crop simulation models and gridded weather data in India

We find that gridded weather datasets vary in their representation of historic spatial and temporal temperature and precipitation patterns, creating large uncertainties in estimated crop yield responses to growing season weather. This highlights the need to consider input data uncertainty in applyin...

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Main Author: CGIAR Platform for Big Data in Agriculture
Format: Informe técnico
Language:Inglés
Published: 2019
Subjects:
models
yields
crop yield
development
simulation models
rural development
data
precipitation
temperature
simulation
systems
weather
uncertainty
agrifood systems
weather data
Online Access:https://hdl.handle.net/10568/122949
Summary:We find that gridded weather datasets vary in their representation of historic spatial and temporal temperature and precipitation patterns, creating large uncertainties in estimated crop yield responses to growing season weather. This highlights the need to consider input data uncertainty in applying crop simulation models with gridded weather data.

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