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Fusion of Simulated and Observational Temperature Data in the Beijing-Tianjin-Hebei Region Based on High-Accuracy Surface Modeling

机译:基于高精度表面造型的京津 - 河北地区模拟和观测温度数据融合

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Temperature changes have a major impact on all aspects of human society and have attracted global attention. The scarcity of observation data and the inaccuracy of the models make obtaining accurate temperature distributions a challenge. This study introduces high-accuracy surface modeling (HASM) combined with temperature simulations from the Weather Research and Forecasting (WRF) model and temperature records from observation stations to investigate the spatiotemporal characteristics of temperature in the Beijing-Tianjin-Hebei region during the period of 1956–2005. Leave-one-out cross-validation is applied to verify the temperature fields before and after the fusion of the models. The results indicate that the WRF model has a limited ability to simulate temperature conditions, but the overall deviation across the region is relatively large. The fusion results of the HASM decrease the mean absolute error (MAE) and the root-mean-square error (RMSE) by half in most instances, and the correlation between the fusion data and observation data is approximately 0.01–0.03 higher than that with the WRF simulation data. Based on the fusion data, obvious warming trends are observed during 1976–2005. In general, temperatures in spring, summer, and autumn increase rapidly from 1996 to 2005 but from 1976 to 1995 in winter. The substantial fluctuations in the interannual temperature during 1996–2005 in summer, autumn, and winter may be related to the frequent occurrence of extreme weather. The spatial distribution of temperature change differs in each season during 1956–1995. A dramatic increase in temperature occurs in the western part of the study area during 1996–2005 but with no seasonal difference.
机译:温度变化对人类社会的各个方面产生了重大影响,并引起了全球的关注。观察数据的稀缺性和模型的不准确性使得获得准确的温度分布是挑战。本研究介绍了高精度表面建模(HASM)与来自天气研究和预测(WRF)模型的温度模拟和从观察站的温度记录相结合,研究了京津冀地区温度的时空特性1956-2005。休留一张交叉验证应用于验证模型融合前后的温度场。结果表明,WRF模型具有有限的模拟温度条件能力,但该区域的整体偏差相对较大。大多数情况下,HASM的融合结果将平均绝对误差(MAE)和根均方误差(RMSE)减少一半,融合数据和观察数据之间的相关性大约高出0.01-0.03 WRF仿真数据。基于融合数据,在1976 - 2005年期间观察到明显的变暖趋势。一般来说,春季,夏季和秋季的温度从1996年到2005年迅速增加,但在冬季1976年到1995年。夏季,秋季和冬季1996 - 2005年期间持续温度的大幅波动可能与极端天气的频繁发生有关。温度变化的空间分布在1956-1995期间的每个季节不同。在1996 - 2005年期间,研究区域的西部发生急剧增加,但没有季节性差异。

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