# Upper Midwest USA Last Millennium Summer 2m Air Temperature #----------------------------------------------------------------------- # World Data Center for Paleoclimatology, Boulder # and # NOAA Paleoclimatology Program #----------------------------------------------------------------------- # NOTE: Please cite original publication, online resource and date accessed when using this data. # If there is no publication information, please cite Investigator, title, online resource and date accessed. # # Description/Documentation lines begin with # # Data lines have no # # # Online_Resource: http://www.ncdc.noaa.gov/paleo/study/17133 # Online_Resource: http://www1.ncdc.noaa.gov/pub/data/paleo/pollen/recons/northamerica/wahl2012/wahl2012-rubylake.txt # # Original_Source_URL: ftp://ftp.ncdc.noaa.gov/pub/data/paleo/pollen/recons/liadata.txt # # Archive: Climate Reconstructions #--------------------------------------- # Contribution_Date # Date: 2014-09-02 #--------------------------------------- # Title # Study_Name: Upper Midwest USA Last Millennium Summer 2m Air Temperature #--------------------------------------- # Investigators # Investigators: Wahl, Eugene; Diaz, Henry; Ohlwein, Christian #--------------------------------------- # Description and Notes # Description: Fossil pollen from three lakes in Wisconsin USA are used (Dark Lake, Ruby Lake, Little Pine Lake) along with modern pollen-climate relationships from the North American Pollen Data Base #--------------------------------------- # Publication # Authors: Wahl, E., H. Diaz, and C. Ohlwein # Published_Date_or_Year: 2012 # Published_Title: A pollen-based reconstruction of summer temperature in central North America and implications for circulation patterns during medieval times # Journal_Name: Global and Planetary Change # Volume: 84-85 # Issue: # Pages: 66-74 # Report Number: # DOI: 10.1016/j.gloplacha.2011.10.005 # Abstract: We present a reconstruction of mean summer temperature for the northern Midwest of theUSA based on lacustrine pollen records from three different lakes in Wisconsin. The results suggest a relatively warm period during the earlier part of the record (~1200–1500 CE) followed by a cooler Little Ice Age (~1500–1900) and a subsequent warming to modern conditions. The reconstructed modern summer mean temperature is in good agreement with observations, and the decades of the 1930s to 1950s appear to be the warmest such period in the proxy record (through 1974). Analyses of circulation features associated with the warmest summers in the recent climate record suggest a prevalence of continental ridging accompanied by generally dry conditions during these warm summers in the Midwest. Drought reconstruction using the Palmer Drought Severity Index (PDSI) and tree-ring records as predictors also yield relatively dry conditions in medieval times for the central US. As reported in a number of recent studies, possible forcing mechanisms include La Niña-like conditions in the equatorial Pacific and warmer than average waters in the tropical Indo-western Pacific Ocean possibly coupled to a positive mode of the AMO/ NAO North Atlantic circulation pattern. #--------------------------------------- # Funding_Agency # Funding_Agency_Name: US National Science Foundation # Grant: 0724619 #--------------------------------------- # Site Information # Site_Name: Ruby Lake # Location: Wisconsin # Country: United States # Northernmost_Latitude: 45.283333 # Southernmost_Latitude: 45.283333 # Easternmost_Longitude: -91.458333 # Westernmost_Longitude: -91.458333 # Elevation: 335 #--------------------------------------- # Data_Collection # Collection_Name: Ruby Lake Temp W12 # First_Year: 1165 # Last_Year: 1965 # Time_Unit: AD # Core_Length: # Notes: Reconstruction using inversion of a climate-to-pollen forward model (the binomial-logistic Generalized Linear Model applied to pollen count ratios) #--------------------------------------- # Chronology: #--------------------------------------- # Variables # Data variables follow that are preceded by "##" in columns one and two. # Variables list, one per line, shortname-tab-longname components (9 components: what, material, error, units, seasonality, archive, detail, method, C or N for Character or Numeric data) ## age_AD ,age,,,years AD,,,, ## temp_2m-JJA-t99% ,2m Air Temperature,,top 99%,degrees C,,Climate Reconstructions,,Binomial-logistic Generalized Linear Model ## temp_2m-JJAmid ,2m Air Temperature,,,degrees C,Climate Reconstructions,Climate Reconstructions,mid-range,Binomial-logistic Generalized Linear Model ## temp_2m-JJA-b99% ,2m Air Temperature,,bottom 99%,degrees C,Climate Reconstructions,Climate Reconstructions,,Binomial-logistic Generalized Linear Model # Data # Data lines follow (have no #) # Data line format - tab-delimited text, variable short name as header # Missing Value: N/A age_AD temp_2m-JJA-t99% temp_2m-JJAmid temp_2m-JJA-b99% 1965 19.78584059 19.5013967 19.24178824 1955 19.98001581 19.6709978 19.39434812 1945 20.49475337 20.07924456 19.75042949 1935 20.39668996 19.95029631 19.59585002 1925 19.97908505 19.61061007 19.2944425 1915 19.99959512 19.63646443 19.3278416 1905 19.61111583 19.24735818 18.90742038 1895 19.79494056 19.44063119 19.12600026 1885 19.6048344 19.24351109 18.90775746 1875 19.26083974 18.94674264 18.62370014 1865 19.74405173 19.43486078 19.16194125 1855 19.12171704 18.86592121 18.59762719 1845 19.37389771 19.10254818 18.83552362 1835 19.57761017 19.31594041 19.07311159 1825 19.11037296 18.86417759 18.61184063 1815 19.55349562 19.27664051 19.01989825 1805 19.20302739 18.94221945 18.67760726 1795 19.64105444 19.38517434 19.14465755 1785 19.49599569 19.21694133 18.95054841 1775 19.76111207 19.47071678 19.20834994 1765 19.26645286 19.01428526 18.76254145 1725 19.48235407 19.21031951 18.94867001 1685 19.8245265 19.4293151 19.07851955 1645 19.25384041 18.95955363 18.65759782 1605 19.51246255 19.18453386 18.87192597 1565 19.91464771 19.57042906 19.26823346 1525 20.26185071 19.88149749 19.567478 1485 20.0464745 19.74668396 19.48679142 1445 19.99040307 19.6777071 19.40687378 1405 19.89692819 19.60330078 19.34454876 1365 19.64690687 19.34470572 19.06095592 1325 19.67189221 19.28538589 18.93059097 1285 19.90414428 19.57164077 19.28214312 1245 19.94991335 19.61363609 19.31953005 1205 19.7149669 19.38172143 19.08040951 1165 19.79697816 19.49892358 19.2289455