The transferability of random forest (RF) and support vector machine (SVM) for estimating daily global solar radiation using long-term data of measured sunshine duration, extraterrestrial solar radiation, and theoretical sunshine duration was evaluated across different climate zones. Root mean square error (RMSE), Pearson correlation coefficient (R), and Lin’s concordance correlation coefficient (LCCC) were applied to evaluate model transferability performance. Generally, RF and SVM gave better transfer performance in the climate zone where they were developed. On average, RF (RMSE = 0.881 kWh/m², R = 0.918, LCCC = 0.885) performed better than SVM (RMSE = 0.93 kWh/m², R = 0.913, LCCC = 0.87) over the study area. RF had narrow ranges of RMSE, R, and LCCC, indicating that RF was more stable for transfer. The transferability performance of RF was mainly affected by the difference in elevation between source and target sites, and SVM was mostly controlled by the distance and difference in elevation between source and target sites. The results indicated that RF might be applied to estimate daily global solar radiation using sunshine duration at the sites within 500 km distance and 1000 m difference in elevation, and SVM within 500 km distance and 500 m difference in elevation between source and target sites.

随机森林 (RF) 和支持向量机 (SVM) 在使用测量的日照时长、地外太阳辐射和理论日照时长的长期数据估算全球每日太阳辐射时的可转移性在不同气候带上进行了评估。均方根误差 (RMSE)、Pearson 相关系数 ( R ) 和 Lin 的一致性相关系数 (LCCC) 用于评估模型的可迁移性性能。一般来说，RF 和 SVM 在它们开发的气候区中提供更好的传输性能。平均而言，RF（RMSE = 0.881 kWh/m ²，R  = 0.918，LCCC = 0.885）比 SVM（RMSE = 0.93 kWh/m ²，R = 0.913, LCCC = 0.87) 在研究区域。RF 的 RMSE、R和 LCCC范围很窄，表明 RF 对转移更稳定。RF的传递性能主要受源站和目标站高程差的影响，SVM主要受源站和目标站高程差的控制。结果表明，RF 可用于利用 500 km 距离内和 1000 m 海拔差异内的站点的日照时数，以及源和目标站点之间 500 km 距离内和 500 m 海拔差异内的 SVM 来估计每日全球太阳辐射。