Urbanization bias III. Estimating the extent of bias in the Historical Climatology Network datasets - Supplementary Information

Supplementary information dataset for the following article: R. Connolly and M. Connolly (2014). <em>Urbanization bias III. Estimating the extent of bias in the Historical Climatology Network datasets</em>. Open Peer Rev. J., 34 (Clim. Sci.), ver 0.1 (non peer-reviewed draft) <strong>Abstract of article</strong> The extent to which two widely-used monthly temperature datasets are affected by urbanization bias was considered. These were the Global Historical Climatology Network (GHCN) and the United States Historical Climatology Network (USHCN). These datasets are currently the main data sources used to construct the various weather station-based global temperature trend estimates. Although the global network nominally contains temperature records for a large number of rural stations, most of these records are quite short, or are missing large periods of data. Only eight of the records with data for at least 95 of the last 100 years are for completely rural stations. In contrast, the U.S. network is a relatively rural dataset, and less than 10% of the stations are highly urbanized. However, urbanization bias is still a significant problem, which seems to have introduced an artificial warming trend into current estimates of U.S. temperature trends. The homogenization adjustments developed by the National Climatic Data Center to reduce the extent of non-climatic biases in the networks were found to be inadequate, inappropriate and problematic for urbanization bias. As a result, the current estimates of the amount of “global warming” since the Industrial Revolution have probably been overestimated.

本数据集为下述论文的补充信息数据集：R. Connolly与M. Connolly（2014）发表于《Open Peer Rev. J.》第34卷（气候科学专题）的《城市化偏差III：估算历史气候站网数据集的偏差程度》，版本0.1（未同行评审草稿）。

**论文摘要**：本研究探讨了两套广泛使用的月均温度数据集受城市化偏差影响的程度，二者分别为全球历史气候学网络（Global Historical Climatology Network, GHCN）与美国历史气候学网络（United States Historical Climatology Network, USHCN）。当前，这两套数据集是构建各类基于气象站的全球温度趋势估算结果的核心数据源。尽管全球气候站网名义上收录了大量乡村站的温度记录，但其中多数记录时长较短，或存在大量数据缺失时段。在近100年中至少有95年完整记录的气象站中，仅有8站为纯乡村站。与之形成对比的是，美国气候站网整体偏向乡村站点，仅不到10%的站点属于高度城市化区域。但城市化偏差仍是一项不容忽视的问题，其似乎为当前美国温度趋势估算结果引入了人为的增暖趋势。研究发现，美国国家气候数据中心（National Climatic Data Center, NCDC）为降低该站网中非气候类偏差而开发的均一化校正方案，在应对城市化偏差时存在不足、不当且易引发问题。因此，当前学界对工业革命以来“全球变暖”幅度的估算，大概率存在高估情况。