Wang Chenghao, Deng Chengbin, Horsey Henry, Reyna Janet L, Liu Di, Feron Sarah, Cordero Raúl R, Song Jiyun, Jackson Robert B
School of Meteorology, University of Oklahoma, Norman, OK, USA.
Department of Geography and Environmental Sustainability, University of Oklahoma, Norman, OK, USA.
Sci Data. 2024 Dec 18;11(1):1383. doi: 10.1038/s41597-024-04238-4.
Reliable and continuous meteorological data are crucial for modeling the responses of energy systems and their components to weather and climate conditions, particularly in densely populated urban areas. However, existing long-term datasets often suffer from spatial and temporal gaps and inconsistencies, posing great challenges for detailed urban energy system modeling and cross-city comparison under realistic weather conditions. Here we introduce the Historical Comprehensive Hourly Urban Weather Database (CHUWD-H) v1.0, a 23-year (1998-2020) gap-free and quality-controlled hourly weather dataset covering 550 weather station locations across all urban areas in the contiguous United States. CHUWD-H v1.0 synthesizes hourly weather observations from stations with outputs from a physics-based solar radiation model and a reanalysis dataset through a multi-step gap filling approach. A 10-fold Monte Carlo cross-validation suggests that the accuracy of this gap filling approach surpasses that of conventional gap filling methods. Designed primarily for urban energy system modeling, CHUWD-H v1.0 should also support historical urban meteorological and climate studies, including the validation and evaluation of urban climate modeling.
可靠且连续的气象数据对于模拟能源系统及其组件对天气和气候条件的响应至关重要，尤其是在人口密集的城市地区。然而，现有的长期数据集往往存在空间和时间上的空白以及不一致性，这给在现实天气条件下进行详细的城市能源系统建模和跨城市比较带来了巨大挑战。在此，我们介绍历史综合每小时城市天气数据库（CHUWD-H）v1.0，这是一个长达23年（1998 - 2020年）的无间隙且经过质量控制的每小时天气数据集，涵盖美国本土所有城市地区的550个气象站位置。CHUWD-H v1.0通过多步骤填补空白方法，将来自气象站的每小时天气观测数据与基于物理的太阳辐射模型的输出以及一个再分析数据集进行了综合。10倍蒙特卡洛交叉验证表明，这种填补空白方法的准确性超过了传统的填补空白方法。CHUWD-H v1.0主要为城市能源系统建模而设计，也应支持历史城市气象和气候研究，包括城市气候建模的验证和评估。
