(C) PLOS One
This story was originally published by PLOS One and is unaltered.
. . . . . . . . . .
Historical archives reveal record rainfall and severe flooding in December 1867 resulting from an atmospheric river and snowmelt, western Washington, USA [1]
['Daniel G. Gavin', 'Department Of Geography', 'University Of Oregon', 'Eugene', 'Oregon', 'United States Of America', 'Patrick J. Bartlein', 'Cary J. Mock', 'University Of South Carolina', 'Columbia']
Date: 2024-02
Validation and analysis of 19th century precipitation observations
We examined daily weather logs from the 19th century at six locations (mainly U.S. military forts) in western Washington and northwestern Oregon (Fig 1). Measurements were likely made using a DeWitt conical rain gauge or a cylindrical rain gauge with a diameter between six and nine inches (150 to 225 mm). Guidance from the Surgeon’s General office indicated that rain gauges were to be located in clear openings and kept at least eight feet (2.44 m) high [18], which is considerably higher than the modern standard of 0.58 m [19]. This would likely result in about 10% reduction of rain measured in the gauge due to wind effects, thus providing a conservative low-end measurement of precipitation [20]. Daily data from three U.S. military forts (Fort Canby, Fort Vancouver, and Fort Steilacoom) were obtained from the Midwestern Regional Climate Center (
https://mrcc.purdue.edu/) and subject to several quality control criteria and outlier verification [21]. As the Midwestern Regional Climate Center dataset does not yet contain all available data, we keyed in additional data from scanned images of original log sheets obtained from the U.S. National Archives from American Camp (San Juan Island), Fort Townsend, and, for 1865-1870, Astoria. The Astoria record is from the U.S. Coast Survey, and its precipitation gauge practices did not have the abnormally high gauge placement problem as the military forts. We conducted additional extreme-value checking by examining comments and temperature values on the data ledgers on the days with high rainfall. On four days (at two locations), high precipitation values were accompanied by a comment of “snow” and temperatures consistent with snowfall. On those days we reduced values to 10% of the reported value assuming a 10:1 snow water ratio.
The 19th century data were compared to nearby Global Historical Climatology Network (GHCN) stations (Fig 1; [22]). Comparator stations were selected as the longest records within several km from the 19th-century observations. For the Astoria comparators, we combined two GHCN stations (Astoria, 1892-1960; < 1 km away; Astoria Regional Airport, 1960-2023; 5 km away). For Fort Canby, American Camp, and Fort Vancouver, the comparator GHCN stations were located 8 km, 23 km, and 6 km, respectively, from the historic observations. For Fort Steilacoom comparators, we combined data from Puyallup 2W Experiment station (1914-1947; 17 km from Fort Steilacoom) and SeaTac Airport (1948-2023; 34 km from Fort Steilacoom). The GHCN daily data were processed as follows: 1) No observations were used if data quality flags indicated potential error, 2) 0.25 mm was substituted for days flagged as trace rainfall, 3) 0 mm was substituted for days flagged as ‘missing presumed zero’. Such flags occurred on a total of 11 days among three stations. An extreme-value checking of the GHCN data, as for the 19th century data, did not identify any suspicious values.
We assessed bias in the 19th century data in two ways. First, we plotted cumulative precipitation for the wet season (01 November to 31 March) for each year in the 19th century data with respect to quantiles and extreme values of cumulative precipitation at the comparator GHCN stations. Only years with observations on all 151 days of the wet season were included. We tested for differences in the median November-March cumulative precipitation between the 19th century data and GHCN data, in which each water year is an observation, using the Mann-Whitney U test. Second, we examined the statistical distribution of wet-day precipitation for the entire set of days with precipitation > 0.5 mm in the 01 November to 31 March period. For each site, we plotted the cumulative distribution for the set of 19th century daily observations and for the GHCN comparator data with respect to their exceedance probability. Differences in mean values may indicate non-stationary climate rather than observer bias, but we expect similarities in the shape of the distributions.
We summarized rainfall using three-day and four-day sums because of their strong correlation with peak streamflow in the region [23]. Frequency-magnitude plots of precipitation sums at the GHCN stations were calculated using the set of the n largest three-day and four-day sums, with no overlap of days, for the n years of record at each station. The resulting frequency-magnitude relationship is not based on annual maximum values, as more than one event may occur in any year. This “partial duration series” produces a more linear power-law relationship than produced by annual-maximum series [24]. Data and analyses are in S1 File.
Analysis of the 19th century data indicated that the greatest magnitude event, at four of the six sites, was during 12-15 December 1867. At Fort Townsend, the 14 December precipitation was not recorded, and it was only recorded for a six-day period at Fort Canby. We compared this event to the GHCN comparator stations by plotting it on the frequency-magnitude relationships constructed from the GHCN data. In addition, a regional rainfall precipitation series from the GHCN stations was constructed from the four locations with daily measurements through the 1867 event. The precipitation for the comparator sites of these four stations was summed daily over their common period (January 1914 through May 2016), then the three-day and four-day precipitation was calculated as for the individual stations and contrasted to the combined magnitude of the peak three-day (13-15 December) and four-day (12-15 December) precipitation in 1867.
[END]
---
[1] Url:
https://journals.plos.org/climate/article?id=10.1371/journal.pclm.0000324
Published and (C) by PLOS One
Content appears here under this condition or license: Creative Commons - Attribution BY 4.0.
via Magical.Fish Gopher News Feeds:
gopher://magical.fish/1/feeds/news/plosone/