42年北极地表温度数据分辨率提升至1公里，助力冻土与冰盖研究。
Four decades of circumpolar super-resolved satellite land surface temperature data
- 用深度各向异性扩散模型，将AVHRR数据从粗分辨率超分辨到1公里。
- 生成了1981-2022年双日覆盖、1公里精度的北极地表温度数据集。
- 适合研究冻土变化、冰盖质量平衡及气候趋势，也适用于未来卫星数据衔接。
地表温度（LST）是陆气能量交换和气候变化监测的关键气候变量，尤其在快速变暖的北极地区至关重要。基于卫星的长期LST记录，如来自高级甚高分辨率辐射计（AVHRR）的全球区域覆盖（GAC）数据，对检测气候趋势必不可少。然而，AVHRR GAC数据的空间分辨率较粗，限制了其在北极细尺度冻土动态等表面过程分析中的应用。本文提出一个42年覆盖整个北极区的新型超分辨率地表温度数据集，通过基于深度各向异性扩散模型的超分辨率算法，将AVHRR GAC数据下放至1公里分辨率。该模型利用MODIS LST数据进行训练，输入为降分辨率数据，输出为原始分辨率数据，并结合高分辨率土地覆盖、数字高程和植被高度图作为引导。最终数据集提供1981–2022年间双日一次、1公里空间分辨率的北极地表温度观测。该数据集显著提升了冻土建模、近地面气温重建及格陵兰冰盖表面质量平衡评估的能力。同时，它支持了MODIS时代前的气候监测，并为未来热红外卫星任务提供了可扩展的数据连续性框架。
原文摘要 · Abstract (English)
Land surface temperature (LST) is an essential climate variable (ECV) crucial for understanding land-atmosphere energy exchange and monitoring climate change, especially in the rapidly warming Arctic. Long-term satellite-based LST records, such as those derived from the Advanced Very High Resolution Radiometer (AVHRR), are essential for detecting climate trends. However, the coarse spatial resolution of AVHRR's global area coverage (GAC) data limit their utility for analyzing fine-scale permafrost dynamics and other surface processes in the Arctic. This paper presents a new 42 years pan-Arctic LST dataset, downscaled from AVHRR GAC to 1 km with a super-resolution algorithm based on a deep anisotropic diffusion model. The model is trained on MODIS LST data, using coarsened inputs and native-resolution outputs, guided by high-resolution land cover, digital elevation, and vegetation height maps. The resulting dataset provides twice-daily, 1 km LST observations for the entire pan-Arctic region over four decades. This enhanced dataset enables improved modelling of permafrost, reconstruction of near-surface air temperature, and assessment of surface mass balance of the Greenland Ice Sheet. Additionally, it supports climate monitoring efforts in the pre-MODIS era and offers a framework adaptable to future satellite missions for thermal infrared observation and climate data record continuity.
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