Abstract Documentary climate data describe evidence of past climate arising from predominantly written historical documents such as diaries, chronicles, newspapers, or logbooks. Over the past decades, historians and climatologists have generated numerous document-based time series of local and regional climates. However, a global dataset of documentary climate time series has never been compiled, and documentary data are rarely used in large-scale climate reconstructions. Here, we present the first global multi-variable collection of documentary climate records. The dataset DOCU-CLIM comprises 621 time series (both published and hitherto unpublished) providing information on historical variations in temperature, precipitation, and wind regime. The series are evaluated by formulating proxy forward models (i.e., predicting the documentary observations from climate fields) in an overlapping period. Results show strong correlations, particularly for the temperature-sensitive series. Correlations are somewhat lower for precipitation-sensitive series. Overall, we ascribe considerable potential to documentary records as climate data, especially in regions and seasons not well represented by early instrumental data and palaeoclimate proxies.
more »
« less
The global historical climate database HCLIM
Abstract There is a growing need for past weather and climate data to support science and decision-making. This paper describes the compilation and construction of a global multivariable (air temperature, pressure, precipitation sum, number of precipitation days) monthly instrumental climate database that encompasses a substantial body of the known early instrumental time series. The dataset contains series compiled from existing databases that start before 1890 (though continuing to the present) as well as a large amount of newly rescued data. All series underwent a quality control procedure and subdaily series were processed to monthly mean values. An inventory was compiled, and the collection was deduplicated based on coordinates and mutual correlations. The data are provided in a common format accompanied by the inventory. The collection totals 12452 meteorological records in 118 countries. The data can be used for climate reconstructions and analyses. It is the most comprehensive global monthly climate dataset for the preindustrial period so far.
more »
« less
- PAR ID:
- 10477363
- Author(s) / Creator(s):
- ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; more »
- Publisher / Repository:
- NSF-PAR
- Date Published:
- Journal Name:
- Scientific Data
- Volume:
- 10
- Issue:
- 1
- ISSN:
- 2052-4463
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
This is a compilation of total monthly precipitation data in total inches for two NOAA weather stations. The Prairie du Sac station data located at the Prairie du Sac dam on the Wisconsin River (43.31 , -89.7283) started with full monthly records being recorded in 1912 with complete monthly records through 2007. In mid-2007 a nearby station was established in Sauk City at the wastewater treatment plant (43.262 , -89.7349) with continuous data from 2008 through the present. The two stations are relatively close (about 3.25 miles apart), and both are slightly more than 4 miles to the west of the centroid of Fish Lake (Dane Co.) a core study lake in the North Temperate Lakes Long-Term Ecological Research Project conducted by the Center for Limnology at the University of Wisconsin-Madison. The compiled monthly records are based on daily NOAA precipitation records available electronically to the public. As a general practice, daily precipitation over weekends and holidays was not regularly recorded at the stations such that cumulative totals were recorded the following workweek day. As such, while the records for each single day were not always accurately recorded, the monthly totals were generally accurate. However, starting in 1996 at the Prairie du Sac station, because the cumulative weekend/holiday precipitation didn’t allow known daily totals, those cumulate weekend/holiday records were not submitted to NOAA so they were recorded as missing data in NOAA’s electronic dataset. To rectify the many months of missing data, pdf’s of the original hand-written monthly submissions were retrieved from NOAA’s archives such that the monthly precipitation totals could be calculated. In the process a few transcription errors in the electronic records of other months were also corrected in this dataset as well as determining a few other monthly records that were missing. Thus, this dataset of monthly precipitation at the two nearby weather stations is complete and hopefully accurate.more » « less
-
Abstract The interior of Dronning Maud Land (DML) in East Antarctica is one of the most data-sparse regions of Antarctica for studying climate change. A monthly mean near-surface temperature dataset for the last 30 years has been compiled from the historical records from automatic weather stations (AWSs) at three sites in the region (Mizuho, Relay Station, and Dome Fuji). Multiple AWSs have been installed along the route to Dome Fuji since the 1990s, and observations have continued to the present day. The use of passive-ventilated radiation shields for the temperature sensors at the AWSs may have caused a warm bias in the temperature measurements, however, due to insufficient ventilation in the summer, when solar radiation is high and winds are low. In this study, these warm biases are quantified by comparison with temperature measurements with an aspirated shield and subsequently removed using a regression model. Systematic error resulting from changes in the sensor height due to accumulating snow was insignificant in our study area. Several other systematic errors occurring in the early days of the AWS systems were identified and corrected. After the corrections, multiple AWS records were integrated to create a time series for each station. The percentage of missing data over the three decades was 21% for Relay Station and 28% for Dome Fuji. The missing rate at Mizuho was 49%, more than double that at Relay Station. These new records allow for the study of temperature variability and change in DML, where climate change has so far been largely unexplored. Significance StatementAntarctic climate change has been studied using temperature data at staffed stations. The staffed stations, however, are mainly located on the Antarctic Peninsula and in the coastal regions. Climate change is largely unknown in the Antarctic plateau, particularly in the western sector of the East Antarctic Plateau in areas such as the interior of Dronning Maud Land (DML). To fill the data gap, this study presents a new dataset of monthly mean near-surface climate data using historical observations from three automatic weather stations (AWSs). This dataset allows us to study temperature variability and change over a data-sparse region where climate change has been largely unexplored.more » « less
-
Abstract Mean daily to monthly precipitation averages peak in late July over eastern Colorado and some of the most damaging Front Range flash floods have occurred because of extreme 1-day rainfall events during this period. Tree-ring chronologies of adjusted latewood width in ponderosa pine from eastern Colorado are highly correlated with the highest 1-day rainfall totals occurring during this 2-week precipitation maximum in late July. A regional average of four adjusted latewood chronologies from eastern Colorado was used to reconstruct the single wettest day observed during the last two weeks of July. The regional chronology was calibrated with the CPC 0.25° × 0.25° Daily U.S. Unified Gauge-Based Analysis of Precipitation dataset and explains 65% of the variance in the highest 1-day late July precipitation totals in the instrumental data from 1948 to 1997. The reconstruction and instrumental data extend fully from 1779 to 2019 and indicate that the frequency of 1-day rainfall extremes in late July has increased since the late eighteenth century. The largest instrumental and reconstructed 1-day precipitation extremes are most commonly associated with the intrusion of a major frontal system into a deep layer of atmospheric moisture across eastern Colorado. These general synoptic conditions have been previously linked to extreme localized rainfall totals and widespread thunderstorm activity over Colorado during the summer season. Chronologies of adjusted latewood width in semiarid eastern Colorado constitute a proxy of weather time-scale rainfall events useful for investigations of long-term variability and for framing natural and potential anthropogenic forcing of precipitation extremes during this 2-week precipitation maximum in a long historical perspective.more » « less
-
Downscaling coarse global and regional climate models allows researchers to access weather and climate data at finer temporal and spatial resolution, but there remains a need to compare these models with empirical data sources to assess model accuracy. Here, we validate a widely used software for generating North American downscaled climate data, ClimateNA, with a novel empirical data source, 20th century weather journals kept by Admiralty Island, Alaska homesteader, Allen Hasselborg. Using Hasselborg’s journals, we calculated monthly precipitation and monthly mean of the maximum daily air temperature across the years 1926 to 1954 and compared these to ClimateNA data generated from the Hasselborg homestead location and adjacent areas. To demonstrate the utility and potential implications of this validation for other disciplines such as hydrology, we used an established regression equation to generate time series of 95% low duration flow estimates for the month of August using mean annual precipitation from ClimateNA predictions and Hasselborg data. Across 279 months, we found strong correlation between modeled and observed measurements of monthly precipitation ( ρ = 0.74) and monthly mean of the maximum daily air temperature ( ρ = 0.98). Monthly precipitation residuals (calculated as ClimateNA data - Hasselborg data) generally demonstrated heteroscedasticity around zero, but a negative trend in residual values starting during the last decade of observations may have been due to a shift to the cold-phase Pacific Decadal Oscillation. Air temperature residuals demonstrated a consistent but small positive bias, with ClimateNA tending to overestimate air temperature relative to Hasselborg’s journals. The degree of correlation between weather patterns observed at the Hasselborg homestead site and ClimateNA data extracted from spatial grid cells across the region varied by wet and dry climate years. Monthly precipitation from both data sources tended to be more similar across a larger area during wet years (mean ρ across grid cells = 0.73) compared to dry years (mean ρ across grid cells = 0.65). The time series of annual 95% low duration flow estimates for the month of August generated using ClimateNA and Hasselborg data were moderately correlated ( ρ = 0.55). Our analysis supports previous research in other regions which also found ClimateNA to be a robust source for past climate data estimates.more » « less
An official website of the United States government

