# St. Lawrence Valley, Quebec 18th and 19th Century Composite Daily Temperature Data #----------------------------------------------------------------------- # World Data Center for Paleoclimatology, Boulder # and # NOAA Paleoclimatology Program #----------------------------------------------------------------------- # NOTE: Please cite Publication, and Online_Resource and date accessed when using these data. # If there is no publication information, please cite Investigators, Title, and Online_Resource and date accessed. # # # Online_Resource: http://ncdc.noaa.gov/paleo/study/16366 # # Original_Source_URL: ftp://ftp.ncdc.noaa.gov/pub/data/paleo/historical/northamerica/canada/st-lawrence2014temp-sources.txt # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Historical #-------------------- # Contribution_Date # Date: 2014-07-07 #-------------------- # Title # Study_Name: St. Lawrence Valley, Quebec 18th and 19th Century Composite Daily Temperature Data #-------------------- # Investigators # Investigators: Slonosky, V.C. #-------------------- # Description_and_Notes # Description: 18th and 19th Century composite historical daily temperature observations from the St. Lawrence River valley, Quebec, Canada. #-------------------- # Publication # Authors: Victoria C. Slonosky # Published_Date_or_Year: 2014-07-07 # Published_Title: Daily minimum and maximum temperature in the St-Lawrence Valley, Quebec: two centuries of climatic observations from Canada # Journal_Name: International Journal of Climatology # Volume: # Edition: # Issue: # Pages: # DOI: 10.1002/joc.4085 # Online_Resource: http://onlinelibrary.wiley.com/doi/10.1002/joc.4085/abstract # Full_Citation: # Abstract: Climatological and meteorological observations in Canada begin in the first half of the 18th century. Continuous daily observations of the weather and climate for the province of Quebec start in the late 18th century. Estimates of daily minimum and maximum temperatures from historical fixed hour observations are provided from regression models based on hourly data from the modern period. Observations of temperature from different locations and observers are compared and regressions models are used to compile a single series of daily minimum and maximum temperatures extending back to 1742, with nearly continuous observations from 1798. Mean, absolute minimum and maximum values suggest considerable variability in the climate over the past two centuries. Based on a variety of climate indicators, exceptionally warm years include 1808, 1848, 1870, 1953 and 1998, while cold years include 1809, 1816, 1818, 1875 and 1904. Analysis of frost days and growing season length suggest a reduction in cold temperatures over past 200 years, while the incidence of cold spells and heat waves has decreased. #------------------ # Publication # Authors: Victoria Slonosky # Published_Date_or_Year: 2014-04-10 # Published_Title: Historical climate observations in Canada: 18th and 19th century daily temperature from the St. Lawrence Valley, Quebec # Journal_Name: Geoscience Data Journal # Volume: # Edition: # Issue: # Pages: # DOI: 10.1002/gdj3.11 # Online_Resource: http://onlinelibrary.wiley.com/enhanced/doi/10.1002/gdj3.11 # Full_Citation: # Abstract: Daily observations of weather and climate for the province of Quebec, Canada, start in the 18th century and continue to the present day. Daily temperature observations from 12 observers ranging from 1742 to 1873 are described here. The frequency distributions of the temperature observations from each of the historical weather journals are examined for data quality and consistency. Adjustments for differing types of exposures, particularly north wall exposures, are developed. It is shown that examination of the daily data distribution can be used to infer information concerning the instruments used and likely exposure in the absence of metadata. Comparisons of the relative frequency distributions of historical and modern hourly observations are used to assess the reliability of the daily historical temperature data, and are able to detect problems with instrument exposure or sampling biases. Historical observations of temperature from the 18th and 19th centuries are shown to be comparable to modern temperature data. These daily observations will be used in further studies to analyse changes in climate and extreme conditions on a decadal to centennial time frame, and will form part of international data sets for the reconstruction and analysis of past climate events. #------------------ # Funding_Agency # Funding_Agency_Name: # Grant: #------------------ # Site_Information # Site_Name: St. Lawrence Valley # Location: North America>Canada>Quebec # Country: Canada # Northernmost_Latitude: 47.0 # Southernmost_Latitude: 45.4 # Easternmost_Longitude: -71.0 # Westernmost_Longitude: -77.0 # Elevation: m #------------------ # Data_Collection # Collection_Name: St-Lawrence2014temp-sources # Earliest_Year: 1742 # Most_Recent_Year: 2010 # Time_Unit: AD # Core_Length: m # Notes: #------------------ # Chronology: # # # #---------------- # Variables # # Data variables follow (have no #) # Data line variables format: Variables list, one per line, shortname-tab-longname-tab-longname components (9 components: what, material, error, units, seasonality, archive, detail, method, C or N for Character or Numeric data) # ##age_AD age, , , AD, , , , ,N ##day Day of Year, , , , , , , ,N ##temp-min surface temperature, , , deg C, daily minimum, , Celsius calculation, ,N ##pd_int1min prediction interval daily minimum 1, , , , , , , to estimate daily minimum from fixed hourly observations,N ##pd_int2min prediction interval daily minimum 2, , , , , , , to estimate Montreal daily minimum temperatures from other sites, N ##notes_source_min source for daily minimum value, , , , , , , ,C ##temp-max surface temperature, , , deg C, daily maximum, , Celsius calculation, ,N ##pd_int1max prediction interval daily maximum 1, , , , , , , to estimate daily maximum from fixed hourly observations,N ##pd_int2max prediction interval daily maximum 2, , , , , , , to estimate Montreal daily maximum temperatures from other sites, N ##notes_source_max source for daily maximum values, , , , , , , ,C #---------------- # Data: # 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19.88 6.88 1.82 gaulthier 1743 142 9.47 6.50 4.08 gaulthier -999.90 0.00 0.00 missing 1743 143 11.06 6.50 4.31 gaulthier 18.36 6.89 2.37 gaulthier 1743 144 8.51 6.50 4.27 gaulthier -999.90 0.00 0.00 missing 1743 145 -999.90 0.00 0.00 missing 24.31 7.26 2.86 gaulthier 1743 146 4.96 6.50 3.91 gaulthier -999.90 0.00 0.00 missing 1743 147 5.43 6.50 4.87 gaulthier -999.90 0.00 0.00 missing 1743 148 6.97 6.50 4.44 gaulthier -999.90 0.00 0.00 missing 1743 149 6.78 6.50 3.86 gaulthier 16.67 6.88 3.43 gaulthier 1743 150 4.49 6.49 5.00 gaulthier 14.63 6.88 2.83 gaulthier 1743 151 2.08 6.49 7.18 gaulthier 14.89 6.89 2.85 gaulthier 1743 152 0.67 6.49 3.71 gaulthier 16.78 6.90 3.90 gaulthier 1743 153 5.52 6.50 4.36 gaulthier 20.37 6.88 3.09 gaulthier 1743 154 8.33 6.50 3.66 gaulthier 19.40 6.88 3.02 gaulthier 1743 155 8.42 6.50 3.95 gaulthier 20.67 6.88 2.68 gaulthier 1743 156 8.73 6.50 3.75 gaulthier 21.84 6.87 1.76 gaulthier 1743 157 9.79 6.50 3.75 gaulthier -999.90 0.00 0.00 missing 1743 158 9.51 6.50 4.71 gaulthier -999.90 0.00 0.00 missing 1743 159 9.02 6.50 4.28 gaulthier -999.90 0.00 0.00 missing 1743 160 10.22 6.50 4.36 gaulthier -999.90 0.00 0.00 missing 1743 161 9.92 6.50 4.49 gaulthier -999.90 0.00 0.00 missing 1743 162 9.28 6.50 4.14 gaulthier 21.00 6.88 2.89 gaulthier 1743 163 8.47 6.50 4.74 gaulthier 19.21 6.88 3.56 gaulthier 1743 164 8.59 6.50 4.22 gaulthier 21.54 6.87 2.09 gaulthier 1743 165 7.89 6.50 3.56 gaulthier 19.88 6.88 2.93 gaulthier 1743 166 7.36 6.50 3.96 gaulthier 22.57 6.88 2.46 gaulthier 1743 167 10.02 6.50 4.00 gaulthier 25.37 6.87 3.53 gaulthier 1743 168 14.70 6.50 3.68 gaulthier 26.21 6.87 2.31 gaulthier 1743 169 12.98 6.50 4.01 gaulthier 26.64 6.86 2.30 gaulthier 1743 170 12.88 6.50 4.36 gaulthier 25.73 6.86 3.31 gaulthier 1743 171 10.54 6.50 4.57 gaulthier 24.92 6.87 2.32 gaulthier 1743 172 9.93 6.50 4.25 gaulthier 20.49 6.88 2.29 gaulthier 1743 173 10.47 6.50 4.13 gaulthier 18.44 6.89 2.93 gaulthier 1743 174 9.64 6.50 3.95 gaulthier 20.24 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191 13.59 6.50 4.51 gaulthier 30.01 6.86 3.70 gaulthier 1743 192 22.40 6.50 4.93 gaulthier 33.51 7.21 4.43 gaulthier 1743 193 19.28 6.50 5.21 gaulthier 27.50 6.97 3.21 gaulthier 1743 194 18.27 6.50 3.60 gaulthier 29.88 6.87 2.52 gaulthier 1743 195 15.07 6.50 3.89 gaulthier -999.90 0.00 0.00 missing 1743 196 17.15 6.50 3.28 gaulthier 25.29 6.97 2.35 gaulthier 1743 197 14.80 6.50 3.54 gaulthier 24.81 6.88 1.62 gaulthier 1743 198 15.00 6.50 3.63 gaulthier -999.90 0.00 0.00 missing 1743 199 15.23 6.50 3.71 gaulthier -999.90 0.00 0.00 missing 1743 200 15.10 6.50 3.02 gaulthier -999.90 0.00 0.00 missing 1743 201 16.50 6.50 3.98 gaulthier -999.90 0.00 0.00 missing 1743 202 18.60 6.50 4.30 gaulthier -999.90 0.00 0.00 missing 1743 203 17.98 6.50 3.94 gaulthier 29.35 6.87 2.89 gaulthier 1743 204 -999.90 0.00 0.00 missing -999.90 0.00 0.00 missing 1743 205 15.85 6.50 3.16 gaulthier 27.90 6.86 1.94 gaulthier 1743 206 16.90 6.50 3.91 gaulthier 28.12 6.87 1.86 gaulthier 1743 207 16.82 6.50 2.90 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1754 354 -21.56 6.50 3.35 gaulthier -999.90 0.00 0.00 missing 1754 355 -19.13 6.50 4.68 gaulthier -999.90 0.00 0.00 missing 1754 356 -13.34 6.50 3.68 gaulthier -999.90 0.00 0.00 missing 1754 357 -8.62 6.50 3.19 gaulthier -999.90 0.00 0.00 missing 1754 358 -5.75 6.50 3.13 gaulthier 1.51 6.89 3.30 gaulthier 1754 359 -5.54 6.50 3.76 gaulthier -999.90 0.00 0.00 missing 1754 360 -9.09 6.50 5.50 gaulthier 0.74 6.89 5.80 gaulthier 1754 361 -11.34 6.50 6.35 gaulthier 0.14 6.89 4.60 gaulthier 1754 362 -6.43 6.50 5.44 gaulthier 3.31 6.89 5.10 gaulthier 1754 363 -10.79 6.50 5.51 gaulthier -999.90 0.00 0.00 missing 1754 364 -20.86 6.50 4.78 gaulthier -999.90 0.00 0.00 missing 1754 365 -15.71 6.50 4.76 gaulthier -999.90 0.00 0.00 missing 1755 1 -999.90 0.00 0.00 missing -999.90 0.00 0.00 missing 1755 2 -999.90 0.00 0.00 missing -999.90 0.00 0.00 missing 1755 3 -999.90 0.00 0.00 missing -999.90 0.00 0.00 missing 1755 4 -999.90 0.00 0.00 missing -999.90 0.00 0.00 missing 1755 5 -999.90 0.00 0.00 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