对 "重新发现的数百万数字化历史海平面气压观测数据 "的更正

IF 3.3 3区 地球科学 Q2 GEOSCIENCES, MULTIDISCIPLINARY Geoscience Data Journal Pub Date : 2024-05-12 DOI:10.1002/gdj3.250
Ed Hawkins, Lisa V. Alexander, Rob J. Allan
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This is an example of issue (4) listed above and suggests that the data at times derived from both a transcribed observation and a change in pressure will contain more errors. The 960 mb at Inchkeith at 15Z on 23rd November also looks too high but is similarly transcribed correctly with no correction reported</i>.</p><p>The revised dataset reduces some of the differences with existing observations for Valentia (original Figure 10) but does not remove all the differences identified between 1922–1929. We also note that one sub-series (London at Kew) in Cornes et al. (Geoscience Data Journal, doi: 10.1002/gdj3.226, 2023) has also been revised in v1.1 of that dataset because of this issue.</p><p>We gratefully acknowledge Richard Meats for bringing this issue to our attention. 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引用次数: 0

摘要

我们修订了与 E. Hawkins 等人的论文 "数百万数字化历史海平面气压观测数据的重新发现"(《地球科学数据期刊》,10, 385, doi: 10.1002/gdj3.163, 2023)相关的数据集。该数据集包括 1919 年 4 月至 1960 年 12 月期间英国和爱尔兰每 3 小时海平面气压的 500 多万个观测数据,这些数据包含在英国气象局发布的《每日天气报告》(DWRs)中。一名数据集用户提请我们注意一个小脚注,其中指出在 1919 年 4 月至 1930 年 2 月的原始 DWR 文件中,给出前 3 小时气压变化的一栏是以半毫巴为单位,而不是我们之前假设的整毫巴。这意味着,在此期间使用 "过去 3 小时的变化 "一栏得出的所有气压观测值都需要进行小幅修订,约占数据集总数的 10%。从1914年5月起,气压单位改为mb,气压变化使用半毫巴。1930 年 2 月以后,气压变化以十分之一mb 为单位,并得到正确使用。1911年1月至1919年3月的DWR气压观测数据仍未得到保存。图1的讨论内容应为:图1是1919年4月5日的DWR页面示例,显示了每天可以得出八个海平面气压观测数据的站点。每个站点都列出了 01Z、07Z、13Z 和 18Z 的气压观测值,其中包括转换为海平面的气压观测值(精度为 0.1 mb)和前 3 小时的气压变化(单位为半毫巴)。这样就可以计算出 22Z、04Z、10Z 和 15Z 的气压,但由于气压变化的精度只有 0.5 毫巴,因此不确定性较小。请注意,这些行并不总是完整的,突出显示了缺失的数据,尤其是 01Z 的数据,因此前一天 22Z 的数据也是如此。数据集的修订意味着图 6、图 9 和图 10 的更新版本在视觉上存在细微差别,但在此不予显示。图 7 的修订版已显示,围绕图 7 和图 8 的讨论现在应为:例如,11 月 23 日 15Z 在苏格兰南部 Eskdalemuir 的缺失观测值为 956 mb,在爱尔兰的其他缺失观测值分别为马林头(Malin Head)的 972 mb 和布莱克索德点(Blacksod Point)的 984 mb。如果要分析特定强风暴的案例研究,恢复这些个别缺失的观测值可能是有价值的。请注意图 7 顶部一行中间面板中的一个几乎肯定是错误的观测值。1928 年 11 月 16 日 15Z 时伯明翰(最低气压值东南方)的 991 mb 观测值没有在 DWR 中列出修正,并且是从原始 DWR 表中正确转录的。18Z 的观测值为 975 mb,这表明比 3 小时前减去了 16 个半大气压(图 8),因此 15Z 的观测值为 983 mb(图 7)。手写的"-16 "极有可能是 "+16",15Z 的观测值实际上是 967 mb,而不是 983 mb;这符合其他可用的同步观测资料。数据集中还会有类似的例子,但在再分析同化中很可能会被剔除。这是上述问题(4)的一个例子,表明有时从转录观测数据和气压变化得出的数据会包含更多误差。11 月 23 日 15Z 英奇基思(Inchkeith)的 960 毫巴气压看起来也过高,但同样转录正确,没有报告修正。修订后的数据集减少了瓦伦西亚(Valentia)与现有观测数据的一些差异(原始图 10),但没有消除 1922 年至 1929 年之间发现的所有差异。我们还注意到,科恩斯等人(Geoscience Data Journal,doi: 10.1002/gdj3.226,2023)的一个子系列(伦敦邱园)也因为这个问题而在该数据集的 v1.1 中进行了修订。我们对这一错误表示歉意,但结论不变。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Corrigendum to “Millions of digitized historical sea-level pressure observations rediscovered”

We have revised the dataset associated with the paper “Millions of digitized historical sea-level pressure observations rediscovered” by E. Hawkins et al. (Geoscience Data Journal, 10, 385, doi: 10.1002/gdj3.163, 2023). The dataset includes more than 5 million observations of sea level pressure every 3 hours from April 1919 to December 1960 over the UK & Ireland which were contained in the Daily Weather Reports (DWRs) published by the Met Office.

A dataset user brought a small footnote to our attention which stated that in the original DWR documents for April 1919 to February 1930, the column giving the pressure change over the previous 3 hours was in units of half-millibars rather than whole millibars as we had previously assumed. This means that all pressure observations during this period derived using the ‘Change in last 3 hours’ column required small revisions – around 10% of the total dataset.

The ‘change over last 3 hours’ column was first introduced in the DWRs in May 1911 when the units of both pressure observations and the change in 3 hours were in/Hg using two decimal places. From May 1914 onwards, the pressure units were changed to mb, with half-millibars used for the change in pressure. After February 1930, the change in pressure was given in tenths of mb, and this was correctly used. The pressure observations from the DWRs for January 1911 to March 1919 remain unrescued.

The discussion of Figure 1 should read:

Figure 1 shows an example DWR page from 5th April 1919, showing the stations from which eight sea-level pressure observations per day can be derived. Each station has a listing for 01Z, 07Z, 13Z and 18Z, with a pressure observation converted to sea-level (given to a precision of 0.1 mb) and a change in pressure over the previous 3 hr in units of half-millibars. This allows the pressures for 22Z, 04Z, 10Z and 15Z to be calculated, but with a small uncertainty as the change is only given with a precision of 0.5mb. Note that the rows are not always complete, highlighting missing data, especially for 01Z, and therefore also for 22Z the day before.

The dataset revision means there are small visual differences in updated versions of Figures 6, 9 & 10, but these are not shown here. A revised version of Figure 7 is shown, and the discussion around Figures 7 and 8 should now read:

For example, the missing observation at Eskdalemuir in southern Scotland at 15Z on 23rd November is 956 mb, with other missing observations in Ireland from Malin Head at 972 mb and Blacksod Point at 984 mb. Recovering such individual missing observations may be worthwhile if analysing case studies of particular severe storms.

Note one almost certainly erroneous observation in the middle panel of the top row of Figure 7. The 991 mb observation for Birmingham (south-east of the lowest pressure values) at 15Z on 16th November 1928 has no correction listed in the DWRs and is correctly transcribed from the original DWR sheets. The 18Z observation is 975 mb, and this is indicated to be minus 16 half-mb from 3 hr earlier (Figure 8), resulting in a 983 mb observation for 15Z (Figure 7). It seems highly likely that the handwritten ‘−16’ should be ‘+16’, and that the 15Z observation was actually 967 mb, rather than 983 mb; this would fit the other available observations of the synoptic situation. There will be other examples such as this in the dataset, but they would likely be rejected in a reanalysis assimilation. This is an example of issue (4) listed above and suggests that the data at times derived from both a transcribed observation and a change in pressure will contain more errors. The 960 mb at Inchkeith at 15Z on 23rd November also looks too high but is similarly transcribed correctly with no correction reported.

The revised dataset reduces some of the differences with existing observations for Valentia (original Figure 10) but does not remove all the differences identified between 1922–1929. We also note that one sub-series (London at Kew) in Cornes et al. (Geoscience Data Journal, doi: 10.1002/gdj3.226, 2023) has also been revised in v1.1 of that dataset because of this issue.

We gratefully acknowledge Richard Meats for bringing this issue to our attention. We apologize for the error, but the conclusions are unchanged.

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来源期刊
Geoscience Data Journal
Geoscience Data Journal GEOSCIENCES, MULTIDISCIPLINARYMETEOROLOGY-METEOROLOGY & ATMOSPHERIC SCIENCES
CiteScore
5.90
自引率
9.40%
发文量
35
审稿时长
4 weeks
期刊介绍: Geoscience Data Journal provides an Open Access platform where scientific data can be formally published, in a way that includes scientific peer-review. Thus the dataset creator attains full credit for their efforts, while also improving the scientific record, providing version control for the community and allowing major datasets to be fully described, cited and discovered. An online-only journal, GDJ publishes short data papers cross-linked to – and citing – datasets that have been deposited in approved data centres and awarded DOIs. The journal will also accept articles on data services, and articles which support and inform data publishing best practices. Data is at the heart of science and scientific endeavour. The curation of data and the science associated with it is as important as ever in our understanding of the changing earth system and thereby enabling us to make future predictions. Geoscience Data Journal is working with recognised Data Centres across the globe to develop the future strategy for data publication, the recognition of the value of data and the communication and exploitation of data to the wider science and stakeholder communities.
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