# Hemispheric 1,000 Year Pseudoproxy Data and Temperature Reconstructions
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#                World Data Service for Paleoclimatology, Boulder 
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#                     NOAA Paleoclimatology Program 
#             National Centers for Environmental Information (NCEI)
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# Template Version 3.0
# Encoding: UTF-8
# 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. 
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# Online_Resource: https://www.ncdc.noaa.gov/paleo/study/23890 
#       Description: NOAA Landing Page
# Online_Resource: https://www1.ncdc.noaa.gov/pub/data/paleo/reconstructions/neukom2018/readme-neukon2018.txt
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# Original_Source_URL:  
#       Description:
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# Description/Documentation lines begin with #
# Data lines have no #
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# Archive: Climate Reconstructions
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# Dataset DOI: 
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# Parameter_Keywords: air temperature
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# Contribution_Date
#	Date: 2018-05-15 
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# File_Last_Modified_Date
#	Date: 2018-05-15 
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# Title
#	Study_Name: Hemispheric 1,000 Year Pseudoproxy Data and Temperature Reconstructions
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# Investigators
#	Investigators: Neukom, R.; Schurer, A.P.; Steiger, N.J.; Hegerl, G.C.
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# Description_Notes_and_Keywords
#	Description: Pseudoproxy data and reconstruction outputs for Neukom et al. (2018). 
#	The data are organized as follows:
#	All proxy data are semicolon separated, with the first column conatining the years, following columns containing the proxy data, header giving their names.
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# Folder Pseudoproxy_data:
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# Statistical pseudoproxies are in the zip folder Pseudoproxy_data.zip. It contains:
# In the main folder one realizatoin of statistical noise proxies for each experiment (SNR and noise-type) and climate model simulation.
# See Table S1 for experiment list and abbreviations.
# The experiment SNRr has the suffix 'ProxyNoise' in the file names.
# The suffix 'ProxyNoiseAR1-cor' corresponds do experiment SNRr-AR1. 
# The suffix 'ProxyNoiseAR1-corTarget' corresponds do experiment SNRrt-AR1. 
# The suffix 'ProxyNoiseAR1' corresponds to an experiment not used in the paper (it uses the AR1 coefficient of the proxy-instrumental residuals instead of the proxy AR1)
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# The sub-folder Ensemble_files contains one sub-folder for each simulation and within these one sub-folder for each hemisphere.
# In each of these subfolders is a file for each proxy records containing the 100 noise realizations for each experiment. These files have no headers.
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# The PSM-based pseudoproxies are in the sub-folder PSM. Including one file for each CESM simulation and hemisphere.
# Infilled versions (over the calibration period), which were used for this paper, are also provided.
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# Folder PPE: 
# this folder contains the pseudoproxy-based reconstructions. It contains one sub-folder for each hemisphere.
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# For each experiment and model simulation there is a file containing the 100-member reconstructions in columns (no header).
# Experiment abbreviations as above, including also one file for the PSM-based reconstructions
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# The folder Real_proxy_recons contains one file for the real-proxy reconstructions for each hemispheres.
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# Publication 
#	Authors: Raphael Neukom, Andrew P. Schurer, Nathan J. Steiger, Gabriele C. Hegerl
#	Published_Date_or_Year: 2018-05-15      
#	Published_Title: Possible causes of data model discrepancy in the temperature history of the last Millennium
#	Journal_Name: Scientific Reports
#	Volume: 8
#	Edition: 7572
#	Issue: 
#	Pages:
#	Report_Number: 
#	DOI: 10.1038/s41598-018-25862-2
#	Online_Resource: https://www.nature.com/articles/s41598-018-25862-2
#	Full_Citation: 
#	Abstract: Model simulations and proxy-based reconstructions are the main tools for quantifying pre-instrumental climate variations. For some metrics such as Northern Hemisphere mean temperatures, there is remarkable agreement between models and reconstructions. For other diagnostics, such as the regional response to volcanic eruptions, or hemispheric temperature differences, substantial disagreements between data and models have been reported. Here, we assess the potential sources of these discrepancies by comparing 1000-year hemispheric temperature reconstructions based on real-world paleoclimate proxies with climate-model-based pseudoproxies. These pseudoproxy experiments (PPE) indicate that noise inherent in proxy records and the unequal spatial distribution of proxy data are the key factors in explaining the data-model differences. For example, lower inter-hemispheric correlations in reconstructions can be fully accounted for by these factors in the PPE. Noise and data sampling also partly explain the reduced amplitude of the response to external forcing in reconstructions compared to models. For other metrics, such as inter-hemispheric differences, some, although reduced, discrepancy remains. Our results suggest that improving proxy data quality and spatial coverage is the key factor to increase the quality of future climate reconstructions, while the total number of proxy records and reconstruction methodology play a smaller role.
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# Funding_Agency 
#	Funding_Agency_Name: Swiss National Science Foundation
#	Grant: PZ00P2_154802
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# Funding_Agency 
#	Funding_Agency_Name: National Centre for Atmospheric Science (NCAS) 
#	Grant: 
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# Funding_Agency 
#	Funding_Agency_Name: Wolfson Foundation
#	Grant: Royal Society Wolfson Research Merit Award (WM130060) 
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# Funding_Agency 
#	Funding_Agency_Name: Royal Society
#	Grant: Royal Society Wolfson Research Merit Award (WM130060) 
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# Funding_Agency 
#	Funding_Agency_Name: NERC under the Belmont forum
#	Grant: PacMedy (NE/P006752/1)
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# Funding_Agency 
#	Funding_Agency_Name: US National Science Foundation
#	Grant: OISE-1743738
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# Site_Information 
#	Site_Name: Northern hemisphere
#	Location: Geographic Region>Northern Hemisphere
#	Country:  
#	Northernmost_Latitude: 90
# 	Southernmost_Latitude:  0
# 	Easternmost_Longitude: 180
# 	Westernmost_Longitude: -180
# 	Elevation:  
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# Site_Information 
#	Site_Name: Southern hemisphere
#	Location: Geographic Region>Northern Hemisphere
#	Country:  
#	Northernmost_Latitude: 0
# 	Southernmost_Latitude: -90
# 	Easternmost_Longitude: 180
# 	Westernmost_Longitude: -180
# 	Elevation:  
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# Data_Collection   
#	Collection_Name: Neukom2018
#	Earliest_Year: 1000
#	Most_Recent_Year: 2000
#	Time_Unit: CE
#	Core_Length: 
#	Notes: 
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# Chronology_Information
#	Chronology: 
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# Variables 
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# Data variables follow are preceded by "##" in columns one and two.
# Data line variables format:  one per line, shortname-tab-variable components (what, material, error, units, seasonality, data type,detail, method, C or N for Character or Numeric data, free text) 
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# Data:
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# Data line format - tab-delimited text, variable short name as header
# Missing Values:  
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