BP神经网络模型在伏旱预测中的应用——以河西走廊为例

利用河西走廊伏旱和伏期降水资料序列,张掖观象台的地面气温、降水、探空等气象资料,以及国家气候中心提供的74个环流因子,借助BP神经网络可以逼近任意非线性函数的能力和特点,构建了一个用于预测伏旱和伏期降水的模型,并对模型的预报效果进行验证。结果表明:BP神经网络模型能够对伏期干旱进行有效地预测,该预测模型对伏旱和伏期降水有比较理想的预报效果,伏旱预报历史拟合率高达97.6%、模型试报准确率为84.6%,伏期降水预测历史拟合率高达97.6%、模型试报准确率为76.9%,其性能指标符合实际要求,具有很好的实际应用价值。

Application of the BP Neural Network Model in Summer Drought Prediction: a case in the Hexi Corridor

Using the summer drought and precipitation data collected in the Hexi Corridor, temperature, precipitation air sounding data from Zhangye Observatory, and circulation factors data from National Climate Center of China, a model to predict summer drought and summer precipitation was established based on BP Neural Network model. BP Neural Network model has comparatively ideal forecasting effect to summer drought and summer precipitation. The simulation results have a consistent rate of 97.6% and 84.6% with summer drought history and forecasting, respectively. The simulation results have a consistent rate of 97.6% and 76.9% with summer precipitation history and forecasting, respectively. So BP Neural Network model has very good actual application capability for summer drought forecasting.