The universal thermal climate index (UTCI) is a crucial temperature index for describing human thermal comfort. With the continuous advancement of Earth observation technologies, it has become feasible to monitor hourly global UTCI at kilometer-level resolution. However, the computational efficiency of UTCI calculations limits the production and application of UTCI, particularly time-series UTCI application at fine resolution. To address the abovementioned issue, this letter proposes a CUDA UTCI (CUTCI) method based on the graphics processing unit (GPU). CUTCI leverages the parallel computing capabilities of GPUs and kernel fusion techniques to improve parallelization and mitigate overhead during calculation. Experimental results demonstrated that, in comparison to operational UTCI and thermofeel UTCI, CUTCI significantly improved computational efficiency by over 250 times and 17 times, respectively. The production of a single-period global UTCI at 0.1° resolution consumed less than 0.2 s. Experimental results revealed that CUTCI holds practical value in supporting real-time UTCI analysis and historical big data analysis over long-time series.

中文翻译：

---

CUTCI：通用热气候指数的 GPU 加速计算方法

通用热气候指数（UTCI）是描述人体热舒适度的重要温度指数。随着对地观测技术的不断进步，每小时千米级分辨率的全球UTCI监测已经成为可能。然而，UTCI计算的计算效率限制了UTCI的产生和应用，特别是高分辨率的时间序列UTCI应用。为了解决上述问题，本文提出了一种基于图形处理单元（GPU）的CUDA UTCI（CUTCI）方法。 CUTCI 利用 GPU 的并行计算能力和内核融合技术来提高并行性并减少计算期间的开销。实验结果表明，与实际运行的UTCI和thermofeel UTCI相比，CUTCI的计算效率分别显着提高了250倍和17倍以上。 0.1°分辨率的单周期全球UTCI的产生耗时不到0.2秒。实验结果表明，CUTCI在支持实时UTCI分析和长时间序列的历史大数据分析方面具有实用价值。