Dataset List

Vol.|Area

No.11 Vol.11,2024
No.10 Vol.11,2024
No.09 Vol.11,2024
No.08 Vol.11,2024
No.07 Vol.11,2024
No.06 Vol.11,2024
No.05 Vol.11,2024
No.04 Vol.11,2024
No.03 Vol.11,2024
No.02 Vol.11,2024
No.01 Vol.11,2024
No.12 Vol.10,2023
No.11 Vol.10,2023
No.10 Vol.10,2023
No.09 Vol.10,2023
No.08 Vol.10,2023
No.07 Vol.10,2023
No.06 Vol.10,2023
No.05 Vol.10,2023
No.04 Vol.10,2023
No.03 Vol.10,2023
No.02 Vol.10,2023
No.01 Vol.10,2023
No.12 Vol.9,2022
No.11 Vol.9,2022
No.10 Vol.9,2022
No.09 Vol.9,2022
No.08 Vol.9,2022
No.07 Vol.9,2022
No.06 Vol.9,2022
No.05 Vol.9,2022
No.04 Vol.9,2022
No.03 Vol.9,2022
No.02 Vol.9,2022
No.01 Vol.9,2022
No.12 Vol.8,2021
No.11 Vol.8,2021
No.10 Vol.8,2021
No.09 Vol.8,2021
No.08 Vol.8,2021
No.07 Vol.8,2021
No.06 Vol.8,2021
No.05 Vol.8,2021
No.04 Vol.8,2021
No.03 Vol.8,2021
No.03 Vol.8,2021
No.02 Vol.8,2021
No.01 Vol.8,2021
No.09 Vol.7,2020
No.08 Vol.7,2020
No.07 Vol.7,2020
No.06 Vol.7,2020
No.05 Vol.7,2020
No.04 Vol.7,2020
No.03 Vol.7,2020
No.02 Vol.7,2020
No.01 Vol.7,2020
No.06 Vol.6,2019
No.05 Vol.6,2019
No.04 Vol.6,2019
No.03 Vol.6,2019
No.02 Vol.6,2019
No.01 Vol.6,2019
No.08 Vol.5,2018
No.07 Vol.5,2018
No.06 Vol.5,2018
No.05 Vol.5,2018
No.04 Vol.5,2018
No.03 Vol.5,2018
No.02 Vol.5,2018
No.01 Vol.5,2018
No.04 Vol.4,2017
No.03 Vol.4,2017
No.02 Vol.4,2017
No.01 Vol.4,2017
No.09 Vol.3,2016
No.08 Vol.3,2016
No.07 Vol.3,2016
No.06 Vol.3,2016
No.05 Vol.3,2016
No.04 Vol.3,2016
No.03 Vol.3,2016
No.02 Vol.3,2016
No.01 Vol.3,2016
No.02 Vol.2,2015
No.01 Vol.2,2015
No.02 Vol.1,2014
No.01 Vol.1,2014
China
Asia
Oceanic region
African
European
North American
South American
Arctic
Global Scale
Data Details

Grid Dataset of High Temperature Days and Types in China (1983-2017)


JIA Zikang1ZHENG Zhihai2FENG Guolin1,2
1 College of Atmospheric Science，Lanzhou University，Lanzhou 730000，China2 Laboratory for Climate Studies，National Climate Center，China Meteorological Administration，Beijing 100081，China

DOI:10.3974/geodb.2021.01.06.V1

Published:Jan. 2021

Visitors：10038       Data Files Downloaded：172      
Data Downloaded：85.63 MB      Citations：

Key Words：

China,high temperature days,types,grid data,1983-2017

Abstract：

Grid Dataset of High Temperature Days (HDs) and Types in China (1983-2017) was developed based on the temperature data from 2374 meteorological stations in China from June to September from 1983 to 2017 and mid-summer data from 750 stations in southern China. Clustering analysis was used to classify the midsummer high temperature types in southern China. The dataset is consisted of 6 data files:(1) annual HDs grid data ,(2) annual average HDs , (3) annual average HDs trend, (4) high temperature classification types in Southern China, (5) inter-annual variation of HDs in Southern China,(6) inter-annual variation of HD types. The dataset is archived in .nc and .txt formats with data size of 2.43 MB (Compressed into one single file with 509 KB). The analysis paper based on this dataset was published at Acta Meteorological Sinica, Vol. 78, No. 6, 2020.Browse

Foundation Item：

Ministry of Science and Technology of P. R. China (2017YFC1502303); National Natural Science Foundation of China (41875101, 41875096)

Data Citation：

JIA Zikang, ZHENG Zhihai, FENG Guolin. Grid Dataset of High Temperature Days and Types in China (1983-2017)[J/DB/OL]. Digital Journal of Global Change Data Repository, 2021. https://doi.org/10.3974/geodb.2021.01.06.V1.

JIA Zikang, ZHENG Zhihai, FENG Guolin. Development of the grid dataset of high-temperature days and types in Southern China (1983-2017) [J]. Journal of Global Change Data & Discovery, 2021, 5(2): 130-134. https://doi.org/10.3974/geodp.2021.02.03.

Data Product:

ID Data Name Data Size Operation
0Datapaper_HDs_1983-2017.pdf78.00kbDownLoad
1 HDs_1983-2017.rar 509.78KB
Co-Sponsors
Superintend