# Asian 1,100 Year Multiproxy Gridded Summer Temperature Reconstructions
#----------------------------------------------------------------------- 
#                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/18635
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# Original_Source_URL: ftp://ftp.ncdc.noaa.gov/pub/data/paleo/contributions_by_author/shi2015/shi2015latlong.txt
# 
# Description/Documentation lines begin with #
# Data lines have no #
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# Archive: Climate Reconstructions
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# Contribution_Date
#	Date: 2015-05-13
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# Title
#	Study_Name: Asian 1,100 Year Multiproxy Gridded Summer Temperature Reconstructions
#--------------------
# Investigators
# 	Investigators: Shi, F.; Ge, Q.; Yang, B.; Li, J.; Yang, F.; Ljungqvist, F.C.; Solomina, O.; Nakatsuka, T.; Wang, N.; Zhao, S.; Xu, C.; Fang, K.; Sano, M.; Chu, G.; Fan, Z.; Gaire, N.P.; Zafar, M.U. 
#--------------------
# Description_and_Notes
#	Description: Gridded and region-wide Asian summer (June-July-August) temperature reconstructions for the past 1,100 years. The reconstructions are based on 357
#	publicly available proxy climate data series from the World Data Center for Paleoclimatology archives (See Shi et al. 2015 supplementary Materials for details).  
#	The gridded reconstructions are at 5 x 5 degree resolution.
#--------------------
# Publication 
# 	Authors: Feng Shi, Quansheng Ge, Bao Yang, Jianping Li, Fengmei Yang, Fredrik Charpentier Ljungqvist, Olga Solomina, Takeshi Nakatsuka, Ninglian Wang, Sen Zhao, Chenxi Xu, Keyan Fang, Masaki Sano, Guoqiang Chu, Zexin Fan, Narayan P. Gaire, Muhammad Usama Zafar 
#	Published_Date_or_Year: 2015-05-09    
#	Published_Title: A multi-proxy reconstruction of spatial and temporal variations in Asian summer temperatures over the last millennium
#	Journal_Name: Climatic Change
#	Volume: 
#	Edition: 
#	Issue: 
#	Pages: 
#	DOI: 10.1007/s10584-015-1413-3
#	Online_Resource: http://link.springer.com/article/10.1007/s10584-015-1413-3
#	Full_Citation: 
#	Abstract: To investigate climate variability in Asia during the last millennium, the spatial and temporal evolution of summer (June-July-August; JJA) temperature in eastern and south-central Asia is reconstructed using multi-proxy records and the regularized expectation maximization (RegEM) algorithm with truncated total least squares (TTLS), under a point-by-point regression (PPR) framework. The temperature index reconstructions show that the late 20th century was the warmest period in Asia over the past millennium. The temperature field reconstructions illustrate that temperatures in central, eastern, and southern China during the 11th and 13th centuries, and in western Asia during the 12th century, were significantly higher than those in other regions, and comparable to levels in the 20th century. Except for the most recent warming, all identified warm events showed distinct regional expressions and none were uniform over the entire reconstruction area. The main finding of the study is that spatial temperature patterns have, on centennial time-scales, varied greatly over the last millennium. Moreover, seven climate model simulations, from the Coupled Model Intercomparison Project Phase 5 (CMIP5), over the same region of Asia, are all consistent with the temperature index reconstruction at the 99 % confidence level. Only spatial temperature patterns extracted as the first empirical orthogonal function (EOF) from the GISS-E2-R and MPI-ESM-P model simulations are significant and consistent with the temperature field reconstruction over the past millennium in Asia at the 90 % confidence level. This indicates that both the reconstruction and the simulations depict the temporal climate variability well over the past millennium. However, the spatial simulation or reconstruction capability of climate variability over the past millennium could be still limited. For reconstruction, some grid points do not pass validation tests and reveal the need for more proxies with high temporal resolution, accurate dating, and sensitive temperature signals, especially in central Asia and before AD 1400.
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# Funding_Agency 
#	Funding_Agency_Name: Chinese Academy of Sciences
#	Grant: XDA05080800, XDB03020500
#------------------
# Funding_Agency 
#	Funding_Agency_Name: National Natural Science Foundation of China
#	Grant: 41301220
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# Site_Information 
#	Site_Name: Asia
#	Location: Asia
#	Country: 
#	Northernmost_Latitude: 57.5
#	Southernmost_Latitude: 2.5
#	Easternmost_Longitude: 142.5
#	Westernmost_Longitude: 62.5
#	Elevation:  m  
#------------------
# Data_Collection   
#	Collection_Name: Shi2015Asia
#	Earliest_Year: 900
#	Most_Recent_Year: 1999 
#	Time_Unit: AD
#	Core_Length: m
#	Notes: 
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# Chronology: 
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# Variables 
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# Data variables follow that are preceded by "##" in columns one and two.
# 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) 
#
## gridnum	Grid Point Number, , , , , , , ,N
## long	Longitude, , , degrees East, , , , ,N
## lat	Latitude, , , degrees North, , , , ,N
#
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# Data:
# Data lines follow (have no #)
# Data line format - tab-delimited text, variable short name as header
# Missing Values:  
# Gridpoint ID numbers and Lat-Long pairs for Shi et al. 2015 gridded asian summer temperature reconstructions
#
gridnum	long	lat
1	97.5	2.5
2	102.5	2.5
3	112.5	2.5
4	77.5	7.5
5	82.5	7.5
6	102.5	7.5
7	77.5	12.5
8	97.5	12.5
9	102.5	12.5
10	107.5	12.5
11	72.5	17.5
12	77.5	17.5
13	82.5	17.5
14	97.5	17.5
15	102.5	17.5
16	107.5	17.5
17	67.5	22.5
18	72.5	22.5
19	77.5	22.5
20	82.5	22.5
21	87.5	22.5
22	92.5	22.5
23	97.5	22.5
24	102.5	22.5
25	107.5	22.5
26	112.5	22.5
27	117.5	22.5
28	62.5	27.5
29	67.5	27.5
30	72.5	27.5
31	77.5	27.5
32	82.5	27.5
33	87.5	27.5
34	92.5	27.5
35	97.5	27.5
36	102.5	27.5
37	107.5	27.5
38	112.5	27.5
39	117.5	27.5
40	122.5	27.5
41	62.5	32.5
42	67.5	32.5
43	72.5	32.5
44	77.5	32.5
45	82.5	32.5
46	87.5	32.5
47	92.5	32.5
48	97.5	32.5
49	102.5	32.5
50	107.5	32.5
51	112.5	32.5
52	117.5	32.5
53	122.5	32.5
54	62.5	37.5
55	67.5	37.5
56	72.5	37.5
57	77.5	37.5
58	87.5	37.5
59	92.5	37.5
60	97.5	37.5
61	102.5	37.5
62	107.5	37.5
63	112.5	37.5
64	117.5	37.5
65	127.5	37.5
66	137.5	37.5
67	62.5	42.5
68	67.5	42.5
69	72.5	42.5
70	77.5	42.5
71	82.5	42.5
72	87.5	42.5
73	92.5	42.5
74	97.5	42.5
75	102.5	42.5
76	107.5	42.5
77	112.5	42.5
78	122.5	42.5
79	127.5	42.5
80	132.5	42.5
81	142.5	42.5
82	62.5	47.5
83	67.5	47.5
84	72.5	47.5
85	77.5	47.5
86	82.5	47.5
87	87.5	47.5
88	92.5	47.5
89	97.5	47.5
90	102.5	47.5
91	107.5	47.5
92	112.5	47.5
93	117.5	47.5
94	122.5	47.5
95	127.5	47.5
96	132.5	47.5
97	137.5	47.5
98	62.5	52.5
99	67.5	52.5
100	72.5	52.5
101	77.5	52.5
102	82.5	52.5
103	87.5	52.5
104	92.5	52.5
105	97.5	52.5
106	102.5	52.5
107	107.5	52.5
108	112.5	52.5
109	117.5	52.5
110	122.5	52.5
111	127.5	52.5
112	132.5	52.5
113	137.5	52.5
114	142.5	52.5
115	77.5	57.5
116	82.5	57.5
117	87.5	57.5
118	92.5	57.5
119	97.5	57.5
120	102.5	57.5
121	107.5	57.5
122	112.5	57.5
123	117.5	57.5
124	122.5	57.5
125	127.5	57.5
126	142.5	57.5