Climate change is closely related to human activities, directly related to regional natural environment change, economic development and social progress, and is a challenge that can not be ignored in regional sustainable development. Temperature change is the most significant indicator of global climate change, and it is an important basic data to analyze and predict climate change.
Based on the CRU global grid data, this data set has prepared 4604 GeoTIFF files of temperature change in China Pakistan Economic Corridor region from 1901 to 2018, in which the temperature unit is ℃, the spatial resolution is 0.5 ° x 0.5 ° and the temporal resolution is month, year and years (1901-2018). This data provides a reference for understanding the spatial-temporal change and trend prediction of temperature in the China Pakistan Economic Corridor Basic data.
collect time | 1901/01/01 - 2018/12/31 |
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collect place | China-Pakistan Economic Corridor Region |
data size | 10.1 MiB |
data format | |
Coordinate system | WGS84 |
Cru weather grid data set, University of East Anglia, UK, version number: v. 4.03
Seven types of spatial data sets of air temperature were generated by format conversion, regional clipping and statistical analysis
(1) The minimum and maximum daily average temperature from 1901 to 2018 are used to produce CPEC respectively_ all_ tmp_ max.tif And CPEC_ all_ tmp_ min.tif Two data files
(2) The annual average daily temperature is named as CPEC_ YYYY_ tmp.tif ;
(3) The naming form of monthly average temperature is CPEC_ YYYYMM_ tmp.tif ;
(4) The monthly average daily minimum temperature was named CPEC_ YYYYMM_ tmn.tif ;
(5) The annual average monthly minimum temperature is named CPEC_ YYYY_ tmn.tif ;
(6) The monthly average daily maximum temperature was named CPEC_ YYYYMM_ tmx.tif ;
(7) The annual average daily maximum temperature is named CPEC_ YYYY_ tmx.tif
Among them, yyyy four digit mark year, mm two digit mark month.
The spatial and temporal accuracy of this data set is consistent with the original CRU data, and the quality is good. It is suitable for climate change research and environmental change analysis.
# | Dataset title |
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# | title | file size |
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1 | data.zip | 10.1 MiB |
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