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首页> 外文期刊>Journal of crop science and Biotechnology >Comparison of Regional Climate Scenario Data by a Spatial Resolution for the Impact Assessment of the Uncertainty Associated with Meteorological Inputs Data on Crop Yield Simulations in Korea
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Comparison of Regional Climate Scenario Data by a Spatial Resolution for the Impact Assessment of the Uncertainty Associated with Meteorological Inputs Data on Crop Yield Simulations in Korea

机译:区域气候情景数据对韩国作物产量模拟相关的影响评价的空间决议。

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Uncertainty of crop yield simulation would be affected by weather input data prepared from different sources of climate datasets. Although regional climate data at a high spatial resolution would be useful for the impact assessment of climate change on crop production, little effort has been made to characterize the uncertainty associated with such climate data in terms of crop yield simulations. The objectives of this study were to compare climate scenario data products obtained from a series of downscaling processes and to identify an overall pattern of uncertainty in these climate data in terms of crop yield simulation. Regional climate scenario data from 2011 to 2014 had a spatiotemporal pattern of uncertainty, which differed by meteorological variables and spatial resolution. Overall, the uncertainty of daily minimum temperature was greater than that of maximum temperature. Daily minimum temperature also had relatively greater uncertainty in an early season of crop production, which could result in the cumulative impact on the uncertainty of crop yield simulations. For the uncertainty of climate data at different spatial resolution, climate data at higher spatial resolution, e.g. 1 km, tended to have lower uncertainty than data at resolutionof 12.5 km did. Still, the uncertainty of regional climate data was relatively similar between data at resolution of 12.5 km and 1 km in major rice production areas in Korea except in areas near Seosan. This merits further studies to examine actual differences in projected crop yields using regional climate scenario data in the future and to assess the impact of uncertainty associated with regional climate data on crop yield simulation.
机译:作物产量模拟的不确定性将受到不同气候数据集的不同来源的天气输入数据的影响。虽然在高空分辨率下的区域气候数据对于对作物生产的气候变化的影响评估有用,但已经努力表征与此类气候数据相关的不确定性,以便在作物产量模拟方面。本研究的目的是比较从一系列较低的过程中获得的气候情景数据产品,并在作物产量模拟方面确定这些气候数据中的整体不确定性模式。 2011年至2014年的区域气候情景数据具有时尚的不确定性模式,其气象变量和空间分辨率不同。总体而言,每日最低温度的不确定性大于最高温度的不确定性。每日最低温度在农作物产量的早期也具有相对较大的不确定性,这可能导致对作物产量模拟的不确定性的累积影响。为了在不同空间分辨率下的气候数据的不确定性,气候数据处于较高的空间分辨率,例如气候数据。 1公里,往往比12.5公里的决议处于决议的数据不确定性较低。尽管如此,在韩国的主要大米生产区,区域气候数据的不确定性在12.5公里,在韩国的主要水稻生产区,除了塞纳兰附近的地区,数据相对相似。这一优点进一步研究了在未来使用区域气候情景数据研究预计作物产量的实际差异,并评估与区域气候数据相关关于作物产量模拟的不确定性的影响。

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