Dataset List

Vol.|Area

Data Details

Grid Dataset of Extreme Temperature Index in China (1961-2020) (V1.0)


CHEN Qiuyuan1ZHANG Yu*1LIU Xiaoyu1LIAN Qinlai1XU Jianjun1
1 South China Sea Institute of Marine Meteorology,Guangdong Ocean University,Zhanjiang 524088,China

DOI:10.3974/geodb.2024.05.06.V1

Published:May 2024

Visitors:7048       Data Files Downloaded:582      
Data Downloaded:205718.96 MB      Citations:

Key Words:

climate change,ETCCDI,Extreme Climate Index,SimmEX

Abstract:

In the context of global warming, extreme weather and climate events occur frequently. In order to unify the definition of extreme climate events in different countries and regions, the World Meteorological Organization (WMO) established the Expert Group on Climate Change Detection and Index (ETCCDI), which provided 27 representative extreme temperature and precipitation indices to regulate research on global extreme climate events. The authors used the daily dataset of basic meteorological elements from China's national ground meteorological station (V3.0) to calculate 16 extreme temperature indices defined by ETCCDI in China, including annual/monthly maximum daily temperature (TXx), annual/monthly minimum daily maximum temperature (TXn), annual/monthly maximum daily minimum temperature (TNx), annual/monthly minimum daily minimum temperature (TNn), warm day percentage (TX90p), cold day percentage (TX10p), warm night percentage (TN90p), cold night percentage (TN10p), summer days (SU), hot night days (TR), and frozen days (ID), Frost days (FD), continuous warm days (WSDI), continuous cold days (CSDI), daily temperature range (DTR), and growth period length (GSL). Then they adopted the angular distance weight interpolation method to obtain the grid dataset of extreme temperature index in China (1961-2020) (V1.0). The resolution is 0.25°x0.25°. The dataset includes: (1) annual data of 16 extreme temperature indices; (2) monthly data of 13 extreme temperature indices. The dataset is archived in .nc format, and consists of 29 data files with data size of 1.43 GB (compressed into one file with 353 MB).

Foundation Item:

National Natural Science Foundation of China (72293604, 42130605); Shenzhen Science and Technology Innovation Bureau (JCYJ20210324131810029)

Data Citation:

CHEN Qiuyuan, ZHANG Yu*, LIU Xiaoyu, LIAN Qinlai, XU Jianjun. Grid Dataset of Extreme Temperature Index in China (1961-2020) (V1.0)[J/DB/OL]. Digital Journal of Global Change Data Repository, 2024. https://doi.org/10.3974/geodb.2024.05.06.V1.

References:


     [1] IPCC. Climate change 2021: the physical science basis [M/OL]. Cambridge: Cambridge University Press, 2021. [2024-05-08]. https://www.ipcc.ch/report/ar6/wg1/downloads/report/IPCC_AR6_WGI_Full_Report.pdf.
     [2] Wu, S. H., Yin, Y. H. Impacts of climate extremes on human systems [J]. Climate Change Research, 2012, 8(2): 99-102.
     [3] Piao, S. L., Zhang, X. P., Chen, A. P., et al. The impacts of climate extremes on the terrestrial carbon cycle: A review [J]. Science China Earth Sciences, 2019(49): 1321-1334.
     [4] Wang, X. L., Hou, X. Y. Raster dataset of extreme temperature in the coastal area of China [J]. Journal of Global Change Data & Discovery, 2019, 3(1): 54-58.
     [5] Ma, W. D., Liu, F. G., Zhou, Q., et al. Development of extreme precipitation dataset of Qinghai-Tibet Plateau (1961–2017) [J]. Journal of Global Change Data & Discovery, 2021, 5(1): 67-72.
     [6] Zhou, Q., Zhang, H. N., Ren, Y. X. Methodology of dataset development on extreme precipitation indexes in Weihe River Basin (1961-2016) [J]. Journal of Global Change Data & Discovery, 2021, 5(1): 62-66.
     [7] Caesar, J., Alexander, L., Vose, R. Large-scale changes in observed daily maximum and minimum temperatures: Creation and analysis of a new gridded data set [J]. Journal of Geophysical Research: Atmospheres, 2006, 111(D5): D05101.
     [8] Dunn, R. J. H., Alexander, L. V., Donat, M. G., et al. Development of an updated global land in situ-based dataset of temperature and precipitation extremes: HadEX3. Journal of Geophysical Research: Atmospheres, 2020, 125(16): e2019JD032263.
     

Data Product:

ID Data Name Data Size Operation
1 SimmEX_1961-2020_1.0.rar 361952.26KB
Co-Sponsors
Superintend