The Impact of Parameterized Convection on the Simulation of Crop Processes
The Impact of Parameterized Convection on the Simulation of Crop Processes
复制标题
参数化对流对作物过程模拟的影响
DOI：
10.1175/jamc-d-14-0226.1
复制
发表时间：
2015
影响因子：
3
通讯作者：
Garcia-Carreras L
中科院分区：
文献类型：
--
作者：
Garcia-Carreras L
全球气候和天气模型是预测未来作物产量的关键工具，但它们都依赖于大气对流的参数化，这往往会对热带地区的降雨特征产生重大偏差。作者通过在不同分辨率下对西非一个作物季节进行区域尺度大气模拟，在有和没有对流参数化的情况下，驱动一年生作物通用大面积模型（GLAM）来评估这些偏差的影响，并将其与观测驱动的GLAM运行进行比较。与观测和对流允许的运行中的短、局部、高强度事件相比，对流的参数化在整个区域产生的降雨量太小且太频繁。持续的小雨增加了地表蒸发，需要更大的降雨量才能启动种植。因此，在参数化对流的运行中，种植被延迟，并且在季节性较冷的时间发生，从而改变了作物所经历的环境条件。即使在高分辨率下，参数化对流驱动的运行低估了现实降雨模式产生的产量的小尺度变化。在用于作物模型之前纠正降雨频率和强度的分布，将改进作物生命周期的过程表示，增加对作物产量预测的信心。这里描述的降雨偏差是对流参数化的一个共同特征，因此，在使用任何全球天气或气候模式时，所描述的作物模式误差都可能发生，因此在使用气候模式相互比较来评估不确定性时仍然隐藏。
Global climate and weather models are a key tool for the prediction of future crop productivity, but they all rely on parameterizations of atmospheric convection, which often produce significant biases in rainfall characteristics over the tropics. The authors evaluate the impact of these biases by driving the General Large Area Model for annual crops (GLAM) with regional-scale atmospheric simulations of one cropping season over West Africa at different resolutions, with and without a parameterization of convection, and compare these with a GLAM run driven by observations. The parameterization of convection produces too light and frequent rainfall throughout the domain, as compared with the short, localized, high-intensity events in the observations and in the convection-permitting runs. Persistent light rain increases surface evaporation, and much heavier rainfall is required to trigger planting. Planting is therefore delayed in the runs with parameterized convection and occurs at a seasonally cooler time, altering the environmental conditions experienced by the crops. Even at high resolutions, runs driven by parameterized convection underpredict the small-scale variability in yields produced by realistic rainfall patterns. Correcting the distribution of rainfall frequencies and intensities before use in crop models will improve the process-based representation of the crop life cycle, increasing confidence in the predictions of crop yield. The rainfall biases described here are a common feature of parameterizations of convection, and therefore the crop-model errors described are likely to occur when using any global weather or climate model, thus remaining hidden when using climate-model intercomparisons to evaluate uncertainty.
提高半干旱热带豆科植物耐旱性的转基因策略
DOI：
--
发表时间：
2009
期刊：
影响因子：
--
作者：
P. Bhatnagar;J. Rao;V. Vadez;K. Sharma
通讯作者：
K. Sharma
萨赫勒地区的中尺度对流系统降雨
DOI：
--
发表时间：
2002
期刊：
影响因子：
--
作者：
Vincent Mathon;H. Laurent;T. Lebel
通讯作者：
T. Lebel
影响因子：
6.4
作者：
Sacks, William J.;Deryng, Delphine;Ramankutty, Navin
通讯作者：
Ramankutty, Navin